A forward deployed engineer joins your team, works inside your real tools and data, and ships the AI system to production. No slide decks, no handoff to someone else.
Most AI pilots never reach production. The model is rarely the reason; the integration, the data and the ownership are.
Closing that gap takes someone who can build the whole system. Snippets brings exactly that: senior full-stack and AI engineering and Claude Partner membership. The engineer who scopes your project builds it and stays on after launch.
// What it is
Designs a solution and hands over recommendations. Someone else has to build it.
Builds from a spec, outside the way your business actually runs, and finds the gaps at launch.
Works inside your tools, data and workflows, ships the system to production and stays until it runs.
// Process
Week 1
Time spent in your real systems and workflows, mapping the steps, the manual workarounds and the edge cases a spec never mentions.
You get:One clearly scoped problem and an agreed definition of success.
Weeks 2 to 3
A first version built against your actual data, plus a test set of real examples that shows where it gets things right and wrong.
You get:A working prototype and proof that it holds up on real cases.
Weeks 4 to 8
Connected to your systems, with guardrails, error handling and monitoring, and rolled out to the people who use it.
You get:A live system your team relies on, monitored from day one.
Final week
Documentation, walkthroughs and a named owner on your side, so the system keeps running and can grow.
You get:A team that can run and extend it without outside help.
Typical timing. The exact plan depends on how many systems are involved.
// The difference
Most AI pilots never reach production: only about 4 in 33 make it, and around 95% show no measurable impact on profit. The approach here is built around the reasons they stall.
Months of strategy workshops before any code is written.
A working version on your real data in as little as 2 weeks.
A polished demo on clean sample data.
Built and tested on your real data and systems from day one, edge cases included.
A one-size platform your team has to adapt to.
Built around how your team already works, inside the tools you use.
Launch, then on to the next client.
Monitoring from day one, a proper handover, and the same engineer on hand after launch.
Describe where it stalled. You'll get a straight answer on what it would take to get it into production.
// Work
An SEO writing platform powered by Claude that helps content teams research, write, and optimize articles at scale. Built on the Claude API with structured outputs for keyword analysis, content scoring, and automated optimization suggestions.
Visit WiseCup Media ↗// From a client
“I highly recommend Pavol as a front-end and back-end developer. He has played a key role in building and optimizing major platforms, creating seamless user interfaces while developing robust, scalable backend systems. His expertise in modern frameworks, problem-solving skills, and attention to detail make him a standout professional. Pavol is proactive, reliable, and an excellent developer who consistently goes above and beyond to deliver high-quality results.”
Sakhib W.Founder & Managing Partner, Verdant Partners// FAQ
When the task is simple and self-contained, or when you already have a mature AI team and only need extra hands. It also can't fix a process that has no owner on your side: someone needs the authority to change how the work is done.
A first working version on your real data can be ready in as little as 2 weeks. Getting it into production usually takes a few more weeks, depending on how many systems are involved.
Access to the systems and data the AI will work with, and one person on your side who owns the outcome and can make decisions about the workflow.
A consultant designs a solution and hands over recommendations. A forward deployed engineer writes the production code, connects it to your systems and stays until it runs.
Mainly Anthropic's Claude, through the Claude API, the Claude Agent SDK and the Model Context Protocol (MCP). Snippets is a member of the Claude Partner Network.
// Get in Touch
Summary
Today is all about who controls the raw materials of AI. OpenAI is catching rivals trying to siphon its hidden reasoning, Reddit is slamming the gate on its data, and Broadcom is lending Anthropic tens of billions to rent Broadcom's own chips. Meanwhile California just told employers a chatbot can't be the one to say 'you're fired'.
Top Stories
OpenAI Says Moonshot-Linked Operators Tried to Siphon Its Hidden Reasoning, Using Over 15,000 Accounts
California Bans 'Robo Bosses': No Firing Workers Based Mainly on AI Output
Broadcom Will Lend Anthropic Up to $42 Billion, and Anthropic Will Use It to Lease Broadcom-Built Chips
Reddit Is Closing Its Public API and Killing RSS, Citing AI-Era Scraping