Software rarely fails because of code alone.
Products fail because teams solve the wrong problem, optimise the wrong constraint, or build systems that can't support growth.
My approach starts with understanding the outcome first:
Only then does technology become useful.
Whether I'm working on a startup product, an AI workflow, or platform infrastructure, the goal is the same: build systems that create business value and remain reliable as complexity grows.
Reduce repetitive work with software, integrations or AI.
Turn an AI capability into a useful product feature or workflow.
Bring APIs, data sources, internal tools and external platforms together.
Take a product from requirements and early decisions to production.
Fix reliability, performance or engineering constraints that are holding the product back.
I work with founders and technical teams to clarify outcomes, define the right technical approach, and build software systems that scale cleanly.
Deploying reliable AI agents and automation systems to handle repetitive business processes: document extraction, customer workflows, and background jobs.
Making AI features fast, dependable, and cost-efficient: implementing fallback logic, evaluation benchmarks, latency optimization, and guardrails.
Bringing platforms, APIs, and tools together: building custom MCP servers, webhook infrastructure, third-party integrations, and real-time data pipelines.
Taking vertical software, web apps, and mobile-friendly experiences from concept to launch with secure backend architectures and clean code.
Production platforms, secure systems, and AI.
Took ASN from a static landing page into a full student platform used across Africa, building the core systems for opportunities, events, resources, community, notifications, saved content, and application tracking. The platform now serves 12,000+ users and 3,500+ community members, cutting mobile data usage by 40% and administrative workload by half.
Founding teams had validated concepts but lacked the engineering capacity to build production-ready software. Embedded with founding teams to architect and ship custom SaaS platforms, AI automation tools, and customer-facing web applications—delivering 4 zero-to-one products from scoping to launch and eliminating months of technical rework.
The platform handled sensitive operational data across multiple commercial clients where a single data leak between tenants would destroy buyer trust. Audited and hardened 30+ system entry points with multi-layered authorization, token controls, and database row isolation—enabling the platform to launch and scale with zero security incidents.
Teams needed instant semantic search across confidential local documents without sending sensitive internal data to third-party cloud APIs. Designed and built an on-device vector search engine using local embeddings and high-performance indexing in Go and Python—delivering sub-10ms query speeds, zero external cloud transfer, and 100% data privacy.
A straightforward engineering approach focused on clarity, reliable delivery, and software that works in production.
What needs to happen, who needs it, and what success looks like.
Turn the requirement into a practical solution and technical approach.
Implement, integrate, test, and iterate.
Deploy the product and make sure it works in the environment where people actually use it.
Use what happens in production to fix, refine, and extend the system.
Technical quality matters because people depend on the product.
Useful AI products need good data, integrations, reliability, evaluation, and sensible failure handling.
The technology should serve what the product or business needs to accomplish.
Honest lessons from building products: what works, what breaks, and why.
Yes. You don't need to write specs or speak tech to work with me. We focus on your business goals and user needs, and I translate those into the right technical decisions while explaining trade-offs in plain English.
Requirements evolve as soon as users touch a product. We work in tight, transparent iterations so we can adjust direction based on direct feedback without throwing away work or blowing up your timeline.
Every build includes automated testing, error tracking, and a post-launch support period. If any issue arises from the delivered scope, I resolve it promptly. I also hand over clear documentation so anyone can maintain the system.
We start with a discovery call to pin down the exact problem and outcome. I then provide a fixed scope, clear timeline, and milestone pricing with zero surprise hourly billing.
I'm Tobi Williams, a software engineer working across product engineering, AI, and backend systems.
I've built production platforms, worked alongside founding teams, and taken software from early requirements through to systems used in production.
My work usually sits where product requirements meet engineering—understanding what needs to be achieved, making the technical decisions required to get there, and building software that can hold up in production.
Bring the problem. We'll clarify the outcome, define the right technical approach, and build a system you can rely on.