“Filip is both fast and exceptionally professional in his communication. I've worked with 20+ developers and Filip stands out as the best experience I've ever had. Will for sure continue to hire.”
Web apps, websites, and AI workflow automation.
AI-native full-stack. From first call to deployed product.
Production systems, not side projects.
Full-stack products, AI workflow automation, data pipelines, and polished client sites. 50+ projects shipped across Upwork and direct engagements.
The Webflow and custom-frontend track that paid for the rest.
Over a dozen client sites, five-star reviews, repeat business.
- Aktiva Aktuel
- Evan Outreacher
- YourExpertly
- Easy Money University
- Design Fantasy
- Austin Pallet Removal
- CA Private · Karl Gustafs
- RDPOOLS
- BIRDLEAD
- Pizza Spot
The receipts.
“Great UpWorker. Highly reliable, dependable, with strong attention to detail. A good fit for any team lucky enough to hire him.”
“I fully recommend Filip to anyone needing development work. Very proficient, very quick. He took initiative in noticing things that could be improved, but never changed anything without getting the green light.”
“Filip is just great. He was so helpful in fixing all the issues on my website. Very knowledgeable, follows good practices and principles, patient and understanding. If you need help with your website, don't look further.”
“Filip has become my go-to website guy. He even found he'd under-estimated the job, but honored his original quote instead of asking for more. That kind of honesty I RARELY see from freelancers.”
“Filip is extremely skilled and knowledgeable with Webflow. He was able to implement what I needed exactly. We appreciated working with him and will work with him again in the future.”
“Great freelancer! Filip did exceptional work on my business website. He executed the project flawlessly, demonstrating expertise in web development, timely delivery, and effective communication.”
“Filip's team stood out for clear thinking, refined design, and a strong analytical approach. In just 2.5 days, they delivered a polished, functional, and well-structured report - a clear 10/10 effort.”
One head owns the whole build. No handoffs, no agency tax, no week-three surprises.
Four ways to bring me into your build.
Each track shipped on real work. Pick the one that maps to your problem.
The right projects are specific enough to ship.
A good first call should answer fit, scope, risk, timeline, and the next concrete step.
Good fit
- You have a manual workflow that costs hours every week.
- You need a production web app, admin panel, POS, dashboard, or internal tool.
- Your data lives across spreadsheets, APIs, Notion, Supabase, or Postgres.
- You want one engineer to own scope, build, deployment, and handoff.
Not a fit
- You only need a quick landing page with no product logic.
- You want an AI chatbot without a clear workflow or business outcome.
- You need a large committee, daily status calls, or agency-style account layers.
- You are not ready to share the current process, tools, or constraints.
Workflow audit
1 to 2 daysMap the current process, identify automation candidates, and leave with a build plan.
Prototype sprint
1 to 2 weeksValidate the riskiest part first: AI output, API integration, data model, or internal UI.
Production build
4 to 12 weeksShip the full app or workflow with auth, data, monitoring, deployment, and handoff.
Four steps, zero theater.
Fewer meetings, clearer scope, faster delivery. The same build in weeks, not quarters.
- 01
Scope in one call
Thirty minutes. You leave with a scope doc, a timeline, and a price.
- 02
Architecture before code
Data models, auth, and integrations laid out before a line is written. No week-three surprises.
- 03
Build with AI, reviewed by hand
Claude Code drafts. I review, refactor, and own every line. That is where the speed comes from.
- 04
Ship, document, hand off
Deploy to your stack, write a handoff README, and stay available after launch.
Questions clients ask before we build.
Short answers on AI agents, automation, full-stack apps, data pipelines, scope, cost, and delivery.
Are you writing the code yourself, or is AI doing it?
Both, deliberately. I architect the system, set the constraints, and review every change. Claude Code and Codex handle most of the typing under that direction. That separation is where the speed comes from. I still write the load-bearing parts by hand: data models, security boundaries, anything where nuance matters more than throughput.
How long have you been working with LLMs?
Since 2022, four years. Started with GPT-3.5 wrappers, moved through Claude 2 and 3, then into agentic work, MCP, multi-tool orchestration, and self-hosted runtimes. The NEXUS rig in the Lab is one of those, a personal agent fleet I own end to end.
Why is this faster and cheaper than an agency?
One head from discovery to deploy means no handoff overhead. Broad-stack architecture experience plus AI-assisted execution compresses the implementation half. Together that lands at roughly half the timeline and cost of an agency on the same scope. The trade-off is bandwidth: I take a small number of engagements at once, not a full pipeline.
Do I need a custom AI agent, or is simpler automation enough?
Probably simpler than you think. Fixed-step workflows fit a script or n8n flow. Tasks that need judgment, research, or messy unstructured data justify an agent. Common candidates either way: lead enrichment, document extraction, reporting, support triage, spreadsheet cleanup. The first call filters what shape the build should take.
How long does a build usually take?
A narrow prototype lands in days. A production workflow in a few weeks. A full-stack product with auth, admin, payments, AI features, and deployment is usually 6 to 10 weeks with AI-assisted delivery, against 12 to 16 in a traditional team. Estimates harden after the first scoping call.
How do you keep AI agents safe with private business data?
I treat an agent like a junior operator with limited permissions. It gets only the tools and data it needs, scoped credentials, audit logs on important actions, human approval where risk is high, and fallback paths when model confidence is low.
Can you fix a messy spreadsheet or manual reporting process?
Yes. Manual reporting often becomes a scheduled Python pipeline, a database-backed dashboard, or an internal admin surface. The right shape depends on data volume, who owns the process, and how often the report has to refresh.
Why hire a solo full-stack builder instead of an agency?
Speed and accountability. Discovery, architecture, implementation, and QA stay in one head. Fewer meetings, tighter scope, direct ownership of the shipped system. Broad-stack range across front-end, back-end, data, and integrations plus AI-assisted execution lands output comparable to a small team at a fraction of the cost.
The fastest way to price a build is to bring one workflow, the current manual steps, and the tools it touches.
Scope a buildReady when you are · 8–12h response
Have a build in mind? Let’s talk.
A thirty-minute call. Bring a rough spec or a vague idea. You leave with a concrete plan and a number.










