Resources
Tips and advice from a seasoned Agency
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Local AI Model Tuning: When It Pays Off and How to Do It
Tuning a model locally means taking an open-weights model, continuing its training on your own examples, and doing all of it on hardware you control. It is realistic today: with LoRA or QLoRA, a 7B or 8B model can be
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How to Reduce LLM Latency in Production Apps
To reduce LLM latency, measure where the time goes first, then work in this order: generate fewer output tokens, stream the response, stop calling a large model for steps that don’t need one, cache repeated prompt prefixes, and only then
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Local vs Cloud AI: How to Choose for Your Business
Local AI runs models on hardware you control. Cloud AI sends every request to someone else’s servers. Neither is better across the board. Local tends to win on privacy, latency and cost at steady, high volume. Cloud wins on peak
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SBOM for Applications: What to Include and How to Keep It Useful
An SBOM (software bill of materials) for an application is a machine-readable list of every component inside it: your direct dependencies, the libraries those pull in, their versions, licenses and the relationships between them. To make one that is worth
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Headless Shopify: Check API Limits and Team Readiness Before You Rebuild
Headless Shopify is worth it only when you need front-end capabilities a theme cannot deliver, or when you have engineering and DevOps capacity to own the result. You trade higher flexibility and potential speed for higher build and maintenance cost.
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Code Audit Pricing: What $500 to $20K+ Buys and How to Compare
Code audit pricing falls into three bands: automated scans run free to $500, focused manual audits typically land between $2K and $5K, and comprehensive audits start around $5K and climb past $20K. The rule behind every quote is simple: the
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GPU Inference Cost: One Ratio Reveals What Your GPU Bill Hides
GPU inference cost is what you pay to run a trained model and generate outputs, and the number that matters most is cost per token, mapped back to the GPU-hour price divided by tokens processed per hour. If you’re not
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Reduce LLM Hallucinations Without Retraining: RAG and CI Gates
The fastest, most reliable way to reduce LLM hallucinations is to ground outputs with retrieval-augmented generation first, add a verification and abstention layer on top, and reserve fine-tuning or contrastive decoding for the errors that survive both. We order it
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RAG Evaluation Datasets for Engineers: Build CI Gates This Quarter
Run FRAMES for multi-hop reasoning, MIRAGE for a compact retrieval-and-generation check, and MTRAG for conversational grounding, then widen the sweep with CRAG and RAGEval or LiveRAG once you know where the system struggles. The posture that makes this work: evaluate
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QA for AI Applications: 3 Engineering Moves From TEVV to CI Gates
QA for AI applications means treating testing as a continuous lifecycle practice, not a one-time pre-launch checklist. The approach we recommend starts with three moves: operationalize TEVV (test, evaluation, verification, validation) across your pipeline, run adversarial and red-team tests against
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Shopify App Security: 8 Checks Developers Need Before Review
To pass Shopify’s app review and protect merchant data, your app needs working OAuth through Shopify’s own libraries, expiring offline tokens, valid TLS everywhere, no open ports facing the internet, high-entropy tokens, HMAC-verified webhooks, minimum necessary scopes, mandatory compliance webhooks,
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AI Developer Staffing: Hiring Managers’ Choice at 12 Months
If you need AI engineering capacity quickly, engage a specialized staffing partner or staff augmentation firm. If you’re building strategic, IP-heavy systems meant to run for 12 months or more, prioritize in-house hires or a retained engineering partner. Either way,
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HIPAA AI Applications: 3 Must Haves U.S. Health Leaders Need
When an AI tool processes protected health information on behalf of a covered entity, HIPAA applies, and that vendor becomes a business associate under the law. Before any rollout, we’d tell you to lock down three things: a signed Business
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3 Controls Engineers Must Fix to Harden LLM Function Calling
Function calling lets a large language model request that your code run a structured action, like querying a database or hitting an API, instead of just generating text. The single highest-priority move: enable strict JSON schemas, expose the smallest possible
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Quantization for Engineers: Ship 4x Smaller Models, INT8/4 Bit Recipes
Model quantization replaces 32-bit floating-point weights and activations with lower-precision formats like INT8 or INT4, cutting memory footprint and compute cost at the price of some accuracy. Done well, INT8 gets you close to a [4x reduction in model size
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Audit Ready LLM Guardrails for Engineers: OWASP to NIST, No Retraining
Guardrails for LLM applications are the layered controls that detect, validate, and constrain model inputs, outputs, and capabilities before they reach a user or trigger an action. In production, the right approach is defense-in-depth: least-privilege mediators sitting between your model
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Workload Driven Vector Database Selection for Engineers: Pilot with p95
The right vector database comes down to one question: what does your workload need most, recall, raw speed, or cost at scale? RAG and search applications should prioritize recall and warm latency, real-time recommendation engines need sub-10ms responses at high
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Engineers: 4 Topologies That Make Multi Agent Systems Reproducible
A multi-agent system (MAS) is a group of autonomous agents that coordinate to solve a task that no single model handles well alone, and testing suites like MAESTRO now show that architecture choice, not agent count, decides whether that coordination
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Map NIST to OCC and FINRA: Model Risk Management for Regulated AI
AI model risk management is the discipline of identifying, testing, and governing the risks an AI or machine learning model introduces before and after it touches production. The single action that matters most right now: adopt a risk-based lifecycle built
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MVP vs Prototype for Product Teams: Save Months with Practitioner Rules
Build a prototype when you need to know if people understand and want what you’re proposing. Build an MVP when you need to know if they’ll actually use it, come back to it, or pay for it. The two tools
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Avoid the 100 Token Limit: Shopify Storefront API for Developers
The Shopify Storefront API is Shopify’s GraphQL-only API for building customer-facing, headless storefronts. Use it for product browsing, cart management, and checkout initiation, and reserve the Admin API for merchant tasks like orders and fulfillment. Authentication is the part teams
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Avoid Failures: NIST Edge AI Deployment Checklist for Engineers
Edge AI deployment means running inference directly on devices or nearby gateways instead of routing every request to a distant cloud server. The payoff is immediate: decisions happen in milliseconds, sensitive data stays local, and bandwidth bills shrink. But the
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CI-Gated LLM Evaluation: 50–100 Sample Readiness Check for Engineers
LLM evaluation is measurable, continuous testing of model outputs and system behavior against task-specific success criteria. Start by picking the 2 to 3 dimensions that matter most for your use case, often faithfulness and latency, then run a readiness check
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30–90–180 Playbook to Harden API Integration Strategy for Engineers
An API integration strategy is a documented, flow-by-flow plan that defines patterns, data contracts, security, and SLOs. Start by inventorying every system you connect to, then prioritize the three flows that touch revenue most directly, and pick an architecture pattern
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Map Data Ownership First: Integrate ERP and Shopify the Operator's Way
Yes, you should integrate ERP with Shopify: use a certified connector if you run a single ERP with standard flows, move to iPaaS middleware once you’re juggling multiple systems or custom pricing rules, and reserve a custom API build for
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Engineers: Cut LLM Prompt Injection Success From Over 50% to Under 2%
Prompt injection is an attack that embeds hidden instructions inside untrusted input, tricking a large language model into ignoring its original instructions and doing something else entirely. It can leak system prompts, exfiltrate data, or trigger unauthorized tool calls in
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Avoid a Six Figure Surprise: Shopify App Cost for CTOs and Founders
A custom Shopify app typically runs in a broad price range from a few thousand dollars for a simple internal tool to well over six figures for an enterprise-grade build with checkout extensions and multi-region hosting. Where your project lands
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Engineers: Ship Agents to Production with a Three Layer AI Agent Framework
The best move in 2026 isn’t picking one AI agent framework. It’s building a layered stack: an orchestration runtime for state and control flow, an agent harness for reasoning and tool use, and an observability layer for tracing what actually
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CTOs: Risk Adjusted Software Development Timeline With 90% Confidence
A realistic software development timeline varies with project complexity, generally shorter for minimum viable products and longer for enterprise systems with multiple integrations. Every one of those ranges assumes a risk-adjusted buffer, not a best-case guess. Scope, integrations, and unresolved
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Engineers: 3 First Moves to Deploy LLMs on Kubernetes with vLLM
The most reliable pattern for Kubernetes LLM deployment is serving your model with vLLM inside a standard Deployment, exposed through a ClusterIP Service, with weights on a PVC and credentials in a Secret. Add the NVIDIA or ROCm device plugin,
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Engineering Teams Playbook: 2026 Code Quality Metrics and CI Gates
Track cognitive complexity, test coverage, code churn, duplication, security findings, and technical debt density. Measure them automatically on every commit, gate the risky ones in CI, and rank remediation by combining churn with metric degradation. Standards like the [TIOBE Quality
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60–80% of Project Time Is Data Prep: Prepare Data for AI With SLAs
AI-ready data is trusted, contextualized, and machine-readable data that an AI system can act on without a human double-checking every output. The first step to prepare data for AI is not picking a vector database or a labeling tool. It’s
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Leaders: See a $20,800 ROI From a Workflow Automation Consultant
A workflow automation consultant maps your repetitive work, decides what should stay human, and builds reliable automations around the rest, usually cutting hours of manual work per week and closing off common error points. Most engagements start the same way:
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Software Architecture Review: Template First Checklist to Surface Risks
A software architecture review is a structured evaluation that surfaces high-impact risks and confirms whether design decisions meet stakeholder quality goals before those decisions become expensive to reverse. The immediate action is to grab the checklist in the next section,
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Stop Pilot Failure: Build Governed, Model Flexible Enterprise AI
Enterprise AI development is the discipline of building production-grade, governed agentic AI systems that run inside real business workflows, not sandboxed demos. The core recommendation is straightforward: prioritize model-flexible architectures grounded in your proprietary data, wrapped in governance from day
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Stabilize Go Live in 1–8 Weeks: Post Launch Support for Startups
Post-launch support is the structured set of activities that stabilizes a product after go-live: monitoring, triage, escalation, and fixes delivered under tighter service levels than normal operations. The right move is a short, time-boxed hypercare window with a named owner
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Ship an MVP Custom Web App in 6–10 Weeks With AI Assisted Engineering
A custom web app is software built from scratch around your specific workflows, data, and users, not a template you skin with your logo. You need one when your business runs on processes that off-the-shelf tools force you to bend
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CTOs: Get Production Ready AI From an AI Software Consultant
An AI software consultant turns strategic AI opportunities into production software and measurable outcomes. The right first step isn’t a full transformation program. It’s a focused assessment or a time-boxed pilot that proves the ROI case before you commit real
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Engineer Playbook: Code Audits and Isolation for Agentic AI Governance
Technical AI governance consulting delivers a hardened production path for AI systems: an audited codebase, a hardened runtime isolated for security, a governed tool registry, enforced guardrails, statistically validated testing, and an incident runbook you can actually execute at 2
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Nine Stages to Fleet Scale AI Change Management for CTOs
AI change management, in the technical sense that matters for production systems, means running every model and its supporting code through a versioned, auditable lifecycle instead of ad hoc deployments. The recommendation is simple to state and hard to skip:
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Stop Debugging Providers at 2 AM: 5 LLM Orchestration Checks
LLM orchestration is the layer of software that coordinates prompts, tools, memory, and multiple model calls into a single reliable workflow, instead of leaving each call to fend for itself. It exists because language models are stateless, single-shot, and unreliable
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99.95% vs 99.9%: Engineers' Checklist to Convert SLOs Into Safe SLAs
An SLI measures what your service is actually doing. An SLO is the internal target you set for that measurement. An SLA is the contract you sign when that target comes with financial consequences attached. Get the SLI right, prove
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CTOs: Stop Deployment Debt. Build an AI App That Survives Six Seams
Hiring a production-focused AI agency is the right move once you need a system that stays reliable after launch, not just a demo that impresses in a boardroom. Before your next vendor call, run a deployment-debt audit and score each
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Refactor Legacy Code in One Sprint Using Tests and Safe AI
The safest, fastest way to refactor legacy code is incremental and test-first: write characterization tests to lock down current behavior, find the seams where you can safely isolate code, and make small reversible changes behind those tests. For larger subsystems,
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8 Week Enterprise AI Integration: Orchestration, Not Model Choice
Enterprise AI integration is the deliberate wiring of AI into your existing systems and workflows to produce measurable gains in speed, accuracy, and decision quality, not a standalone model deployment. It only works when three things are in place: clean,
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Plan for $40k–$1.5M: 2026 Custom Software Costs, AI Drivers & TCO
A small MVP typically runs $40,000 to $150,000, a mid-size business app lands between $150,000 and $400,000, and enterprise platforms often start at $400,000 and climb past $1.5 million. If a vendor quote lands outside these bands without a clear
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2M+ Tokens a Day? Self Hosted LLM Decision Framework for Teams
If you process more than roughly 2 million tokens a day, need strict data control, or need sub-150ms responses, a self-hosted or hybrid setup earns its keep. If you’re under that volume with no compliance mandate, a managed API is
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Shopify Chatbot: Launch Inbox in a Week, Build Custom When Needed
Start with Shopify Inbox. It’s free, it’s built into your admin, and it handles the repetitive stuff (order status, shipping windows, return policy) without any setup fuss. Layer in a third-party app or custom development only when you need proactive
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CTOs: Integration First CRM Workflow Automation, Week One Audit
Production-grade CRM workflow automation now means agentic AI systems that orchestrate integrations and decisions across your software stack, not scripted point automations. The right way to build one is to treat it like any other engineering project: run an Integration
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Ship Agentic Workflows Without an In House Platform Team for Engineers
Agentic workflows combine autonomous AI agents with orchestrated execution logic so software systems can take goal-directed action, not just generate text. The payoff is real: repetitive, judgment-heavy engineering work like triage, log analysis, and PR review can run with far
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Enterprise AI Agent Orchestration: 5 Patterns to Avoid Failures
AI agent orchestration is the control layer that coordinates multiple autonomous agents so they act as one reliable system instead of a pile of scripts talking past each other. It handles task routing, shared state, and enforcement so agents hand
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Three Question Diagnostic: AI Agents vs RPA for IT Architecture
Use RPA for deterministic, high-volume tasks with structured inputs, and use AI agents for unstructured, judgment-heavy work that keeps breaking your scripts. Many enterprise automation programs combine the two: agents typically handle interpretation and decisioning, while RPA executes deterministically. Below
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SLSA Framework: Reach Level 2 in Days; Map Levels to CI/CD Builders
SLSA (Supply-chain Levels for Software Artifacts) proves that a software artifact was built the way its producer claims, using signed provenance and a four-level assurance scale. It works for anyone building, shipping, or consuming code, from a two-person startup to
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Decide Build vs Buy AI Fast: Governance, Hybrid Framework for Leaders
Default to buying or a buy plus build hybrid for most AI capabilities. Build only when the feature runs on proprietary data, delivers competitive differentiation you can defend for years, and you can staff the ongoing engineering. Flip to build
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Human-in-the-Loop AI: When Machines Need a Human Veto
Human-in-the-loop AI means a system routes specific decisions to a person for review, correction, or approval before or after the model acts. Teams need it when a decision is high-stakes, uncertain, or agentic enough that a wrong output causes real
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Shopify Checkout Customization: What to Pick and Why
There are four practical ways to handle shopify checkout customization: the checkout and accounts editor (visual branding and app blocks), checkout apps and Checkout UI extensions (merchant-facing blocks and post-purchase offers), Shopify Functions (server-side discount, shipping, and validation logic), and
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Prompt Caching for Production LLM Systems: A Full Guide
Prompt caching reuses previously computed model state, prefix tensors or full cached responses, so repeated prompts skip recomputation. That cuts input-token cost and latency whenever your traffic has stable prefixes or repetitive semantic intent behind it. It doesn’t help everything:
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When a Fractional AI Team Gets You to Production Faster
A fractional AI team gives you senior AI engineering capacity, on demand, without the six-month hiring cycle or the full-time salary commitment. You get architects, ML engineers, and MLOps specialists who’ve shipped production AI before, working on your priorities for
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AI Workflow Automation: The Enterprise Guide That Works
AI workflow automation pairs autonomous agents with governed process orchestration to execute, verify, and correct business tasks end to end, not just trigger single steps. It works best when a company has a repeatable, high-volume process with clear decision points,
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Technical Debt Remediation: A Playbook for the AI Era
Technical debt remediation is the disciplined process of identifying, measuring, prioritizing, and fixing the shortcuts buried in your codebase, and the goal isn’t a spotless repo. It’s restoring delivery velocity and cutting operational risk. The single most important move you
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Software Maintenance Plans: A Practical Checklist for IT Managers
A software maintenance plan is a formal document that governs how a system gets patched, updated, monitored, and eventually retired, so reliability doesn’t depend on tribal knowledge or whoever’s on call that week. It should belong to one named owner,
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Data Residency vs Sovereignty: A Compliance Guide
Data sovereignty is about which country’s laws can reach your data. Data residency is about which country your data physically sits in. They overlap constantly and get treated as synonyms, which is exactly how compliance programs end up with gaps
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AI Incident Response Needs Its Own Playbook, Not a Patch
Adapting incident response for AI systems means expanding the standard NIST lifecycle with an AI-specific taxonomy, telemetry built for prompts and model behavior, staged remediation, and a pre-vetted open-weight model on standby for forensics. That last piece surprises most teams,
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Data Governance for AI: A Framework for Decision-Makers
Data governance for AI is the set of policies, controls, and roles that determine what data trains, retrieves, or reaches an AI system, and who is accountable when something goes wrong. It differs from traditional data governance because AI systems
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Application Security Assessment: A Practical Guide for Engineers
An application security assessment is a systematic evaluation of an app’s code, configurations, dependencies, infrastructure, and APIs designed to find exploitable weaknesses and prioritize fixes by business impact. Start here:
- Define scope and identify sensitive data (PII, payment info,
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Legacy System Modernization: A Practical Roadmap for IT Leaders
Legacy system modernization is the process of replacing, restructuring, or extending outdated software systems to meet current business, security, and performance demands. If you’re running critical monoliths or aging mainframes, the most useful thing you can do right now is
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AI Workflow Integration: A Decision-Maker's Plan
Integrate AI into a workflow when the process is high-volume, repeatable, and measurable — and start with a pilot narrow enough to prove value in a matter of weeks rather than many months. If a workflow can’t be measured today,
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Last Mile Development: We Get You Across the Line
You Made an App with AI and it has Issues? We Can Solve Them.
You spent a weekend in Cursor. Or perhaps, you spent an afternoon with Claude. Maybe you spun up something in Bolt or Lovable, and watched thousands of lines of code appear in minutes.
It worked. It was incredible. You showed it to your team. Maybe you showed it to a customer. Everyone nodded. This felt like the future.
Then you tried to deploy it.
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Local Models Are the Future (And Most Businesses Don't Know It Yet)
How to leverage AI without spending tokens and leaking data
The first wave of AI adoption was about access. Sign up for ChatGPT, buy a Copilot seat, connect an API, paste in your data, and move on.
For a lot of businesses, that was enough to get started.
The next wave is about ownership. Once AI stops being a demo and starts touching real workflows, the questions get harder:
- Where does our data go?
- Who can access it?
- Are we helping train someone else’s model?
- What happens when pricing or rate limits change?
- Can we use this with source code, contracts, financial records, or customer data?
Those are business questions now, not hypotheticals.
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Eat Your AI Slop, Piggy
This article was written by AI.
Or maybe it wasn’t.
Maybe I wrote every sentence and asked AI to critique the structure, tighten the prose, and suggest a better title? Maybe AI wrote the first draft and I rewrote most of it. Maybe it only fixed a few commas.
Can you tell?
Increasingly, the answer is no. And more importantly—does it matter?
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Open the Black Box: Why Every AI Application Needs a Professional Code Audit
AI has fundamentally changed software development.
Today, almost anyone can build an application with the help of large language models. A few prompts can generate thousands of lines of code, connect APIs, create databases, and produce a working prototype in hours instead of weeks.
That’s the easy part.
The difficult part is knowing whether any of it should be trusted.
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The 6 Best Payroll Options for Psychiatry Practices Using IntakeQ in 2026
A ranked comparison of provider payroll workflows for IntakeQ practices — originally published on PayrollQ.
Cross-posted from PayrollQ.co.
Most payroll software is built for hourly W-2 employees at a restaurant or retail store. Almost none of it is built for how a psychiatry practice actually pays providers (e.g. revenue share, per-appointment rates, hybrid models, and pro bono adjustments) pulled from IntakeQ or PracticeQ billing data.
We put the most common approaches through the same test: how accurate are provider payouts, how much admin time do they take, and can a growing practice trust the numbers when a provider disputes a check? Here is how they stacked up for psychiatry groups, solo practices, and multi-provider mental health clinics using IntakeQ in 2026.
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The 7 Best Website Builders for Dental Practices in 2026
A ranked comparison of website builders for local dental offices — originally published on JumpSites for Dentists.
Cross-posted from JumpSites for Dentists.
Most website builders are built for online stores, restaurants, or design portfolios. Almost none of them are built for the way a dental practice actually gets patients, which is local families searching on their phone, finding your office, and calling to book that same day.
We put the most popular builders through the same test: how fast can a busy dentist get a real, working website online, and will that site actually bring in new patient calls? Here is how they stacked up for general dentists, periodontists, orthodontists, endodontists, and pediatric practices in 2026.
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The 7 Best Website Builders for Contractors and Trade Businesses in 2026
A ranked comparison of website builders for local trade businesses — originally published on JumpSites for Pros.
Cross-posted from JumpSites for Pros.
Most website builders are built for online stores, restaurants, or design portfolios. Almost none of them are built for the way a contractor actually gets work, which is local customers searching on their phone, finding your business, and calling you that same day.
We put the most popular builders through the same test: how fast can a busy trade business owner get a real, working website online, and will that site actually bring in calls? Here is how they stacked up for contractors, plumbers, electricians, handymen, roofers, and other trade pros in 2026.
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How to Outsource Your Software Projects Successfully
For many small business owners, software development is key to driving efficiency, innovation, and a competitive edge. Yet deciding how to build and maintain custom software isn’t always straightforward. In this post, I’ll explore the real cost of outsourcing your software project by comparing the benefits of working with a trusted agency versus the headaches of managing independent contractors—and explain why partnering with a small, proven team might be your best move.
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When to Fire your Developers
As we near our 10-year anniversary in business, having delivered hundreds of successful products, I find myself reflecting on the life span of the client - developer relationship. Today, a business has more options than ever when selecting a development partner. If you are fortunate enough to maintain a website or application long enough, inevitably the key contributors will change. Here are a few thoughts on when to part ways.
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How Much Does It Cost to Develop an App in 2025?
Are you considering developing an app this year? If so, you're likely wondering about the cost. Fortunately for app buyers, the overall cost to develop web and app technology is declining. Or, more aptly, the time and cost to develop an app of a given complexity has been reduced as some of that time can now be saved using improved tooling, such as AI. Therefore, this might be an ideal time to start a project.
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A Trusted Technical Partner is Critical for a Non-Technical Startup Founder
As a startup founder, you have a lot on your plate. From developing your product or service to building a customer base, and raising funds, there are many challenges to navigate. As a non-technical founder running a tech startup it’s critical to have a supportive and trusted partner as you navigate decisions that may not be second nature. You might be fortunate enough to have a technical co-founder. If not, you can rely on angel investors, consultants, or contractors. Here are five reasons why a trusted tech partner is critical for a nontechnical startup founder:
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Keep it Static Stupid — Simple Sites Make Happy Clients
The internet is broken. We arrived here mostly as a matter of habit — a pattern that needs to change.
Your workflow is the problem
A few years back (15?) developers and designers were introduced to an amazing, paradigm-shifting technology called a CMS (content management system). You know many of them by name (WordPress, Drupal, Joomla, etc.), and today they house a significant share of the web’s content.
Why did the CMS take over? Before them most pages were written very simply — with a text editor. Content had to be manually updated on every page, and developers needed to keep track of every change to make sure that repeated elements were updated throughout a site.
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Why your business can’t afford a freelance web developer
I'm going to lead this post with a disclaimer: I’m a recovering freelancer.
I’ve built hundreds of small sites for clients, friends, and family over the years. Friends of mine are freelancers. And I’ve hired dozens of freelancers over the years while running development teams here at Bowtie.co and other companies. I genuinely appreciate the impact that freelance work has had
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When it’s time to ditch your DIY website
“If you really want to grow as an entrepreneur, you’ve got to learn to delegate.” – Richard Branson
Technology is amazing. Every year we discover new ways to automate mundane tasks and simplify the creation of everything that humans produce.
The web is no exception. We also find new tools to tell our brand story, and connect with an increasingly more connected audience. Nearly every day a new tool comes along to strengthen the voice or promotion of your brand, and to make it easier for customers to show their support.
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DVLP/DNVR Hosts ⋈ BowTie Panel
Getting real about frameworks and shortcuts with Denver's top creative and technical talent.
Our founder Chad Person is participating on a panel discussion with Matt Vogels from Webflow _(now [Zestful](https://zestful.com/))_, and Jason Waldrip from [Brand Folder](https://www.brandfolder.com/), for a discussion about creativity, originality, and inspiration in the age of ubiquitous frameworks and technology designed to do your job for you.
Join us for a discussion sure to rouse your mind, ignite your senses, and light a fire under your standing desk. _"If you can make anything, why make anything at all..."_ will take place at the *DVLP/DNVR* conference on *August 4th, 2016*. For more information, visit [the Develop/Denver](https://developdenver.org/)
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Chad Person talks inspiration and grit with the CO AMA
Why 'Do what you love' is stupid, and how to follow your inner genius.
Have you heard the expression 'Do What You Love'? It's become a bit of a rallying cry for a new generation of entrepreneurs.
Tonight, Chad Person, the CEO and Creative Director of Bowtie.co will discuss this rallying cry in relation to his 10 year career as a designer, artist and creative entrepreneur at RECESS an event produced by the Colorado AMA.
RECESS, an evening of learning and inspiration happening, takes place at the Denver Art Museum, 100 W 14th Ave Pkwy, Denver, CO 80204 at 6:00 PM.
Person will be joined by local creative giants, including comedian Debbie Scheer, gardener/poet/ DJ Cavem, and William Espey – Branding Voice Lead for Chipotle.
For tickets, or more information visit the [RECESS website](https://recess.coloradoama.com/).
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Celebrate Denver on Digital Agency Day
Join BowTie in celebrating the best Digital Agencies in Denver.
There are some incredible agencies doing great work in the realm of digital marketing. On January 28th, HubSpot and Unbounce are producing a day of online presentation and community-run events. To celebrate Denver's agencies and their hard work, BowTie is hosting Celebrate Denver (https://digitalagencyday.bowtied.io) - a happy hour and networking event at the end of Digital Agency Day.
What is Digital Agency Day?
The day will be full of both in-person and virtual events that highlight agency growth, strategy, and trends. If you go to Digital Agency Day's website (https://digitalagencyday.com/), you're able to upvote your topic of interest to be covered by industry experts. Then, on Digital Agency Day, you can tune in to watch any of the 8 chosen headline presentations. If you have any questions surrounding they day, the organizers have provided the hashtag #DigitalAgencyDay.
Celebrate Denver
BowTie's community networking event will be held at Galvanize Golden Triangle at 5pm in the Gather cafe. The BowTie team will be there ready to talk digital marketing and take your questions about the future of the static web. It's free to attend, and snacks and beverages provided. Be sure to [RSVP](https://digitalagencyday.bowtied.io/), see you then!
Join us at 5pm, January 28th at Gather in Galvanize GT (map).
Register here
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Partnering with Name.com to Hack the Dot
Do you Hack.social?
Hack the Dot is a two-hour hackathon backed by Name.com. The event is a unique mix of hacking, community building, and ridiculous fun.
Participants are asked to show up and ship a project based on a _secret domain name_ revealed the night of the event. The theme at Hack the Dot Portland, hosted by QuickLeft, was 'hippo.haus' - which not surprisingly, yielded high energy and hilarious projects.
Bowtie has been supporting Hack the Dot with a special 'pitch page' template that's helped lead more than one team to victory.
If you didn't join us in Denver, Seattle, or Portland, you can still meet us at Hack the Dot - San Francisco on December 10th. The event is sold out, but you can register for the wait list here. * I'm also fairly certain that if you show up day of, no one will toss you out ;)
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Adobe Creative Jam selects Chad Person as judge
Join our co-Founder for a night of inspiring design in Albuquerque for the Adobe Creative Jam.
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