AI Product Rescue

I make agentic AI shippable.

MacLeodLabs rescues AI products stuck between demo and market.

I audit messy codebases, expose the real launch blockers, fix the critical path, and get agentic AI systems ready for customers, investors, and production use.

For teams whose AI product works in demo but is not yet reliable, secure, scalable, or trusted enough to ship.

Product rescue · AI security · RAG and document intelligence · Voice AI · Cloud and platform architecture · Hands-on CTO execution

Featured field note
The Manager as Compiler

The Manager as Compiler

WorkSpec: the missing control layer for AI work

AI does not just change how work is produced. It changes how work must be specified, reviewed, constrained, and accepted. The problem is no longer output. The problem is control.

Read the article

Examples of pain points I've fixed

These are not abstract demos. They are recurring failure patterns I have fixed inside real AI products: codebases moving faster than control, agentic systems with invisible risk, voice AI that breaks outside the demo, and RAG/search systems users cannot trust. They are examples, not the full list — the same approach applies wherever an AI product has to get reliable, secure, and trusted enough to ship.

AI codebases moving faster than control

AI coding tools and agents create speed, but they also create fragile code, weak tests, phantom references, unclear ownership, and build instability.

I audit the codebase, identify the launch blockers, repair the critical path, and put quality gates around the parts that matter.

An edit-compile-run-debug loop traces across a live code graph: a node changes, the build fans out, tests fire, a failure lights up, and the agent patches and re-runs — the inner loop of agentic coding, made legible.

Code harnesses, agentic coding workflows, AI-generated code control, codebase rescue, and release-readiness checks.

See how the control loop works

Agentic systems with invisible risk

Agentic AI risk hides across tools, memory, retrievers, APIs, files, permissions, prompts, and human approval boundaries.

I map what the system can read, write, call, trigger, or leak — then fix the control gaps before launch.

A code property graph assembles node by node — functions, variables, and calls — then a taint path lights up and threads from an untrusted source through the graph to a sensitive sink, the way a CPG exposes an attack path.

Code property graphs, trust-boundary mapping, control-surface analysis, agent permissions, and AI security review.

See how the risk map works

Voice AI that works in demo but not production

Voice AI breaks on latency, silence detection, streaming, transcription quality, turn-taking, inference cost, telephony, deployment, and real users.

I turn fragile voice prototypes into production-ready pipelines.

A live sales call, annotated in real time: the pipeline transcribes the client–salesperson conversation and categorizes each exchange against four different sales strategies as the call unfolds. The annotator also lets the user mark key parts of the call by hand — those annotations feed back in to train the AI.

Real-time speech, VAD, streaming, inference acceleration, call handling, deployment, and production-readiness.

See how voice becomes production-ready

RAG and search systems users cannot trust

Naive RAG gives plausible answers. Shippable RAG gives grounded, complete, cited, testable answers — and knows when to abstain.

I rescue document-intelligence systems that miss evidence, hallucinate specifics, fail exhaustive queries, or cannot prove where answers came from.

Standard · single model
Advanced · open-weights SOTA frontier
One query forks two ways: a vector path drifts through an embedding cloud to nearest neighbors while a structured-filter path snaps a metadata grid down to qualifying rows; the two streams converge and rerank into a single ordered result.

Hybrid retrieval, structured filtering, citation grounding, exhaustive search, evaluation, and trustworthy document intelligence.

See how trustworthy retrieval works

Start with a Product Rescue Diagnostic

The diagnostic is for teams with an AI product, prototype, or codebase that needs technical truth before it can ship, sell, fundraise, or scale. I review the codebase, architecture, launch path, control surface, retrieval quality, deployment risks, and operational readiness.

You get a clear answer to three questions

  • What is really blocking launch?
  • What must be fixed now?
  • What can safely wait?

Deliverables

  • Codebase and architecture audit
  • Launch-blocker map
  • Risk register
  • Critical-path fix list
  • Cut / fix / defer recommendations
  • 30-day rescue plan
  • Go / no-go release judgement
  • Optional hands-on rescue sprint
Book a Product Rescue Diagnostic

Senior enough to make the hard calls. Hands-on enough to fix the code.

I have spent decades building systems where being wrong was expensive: trading, banking, cloud platforms, DevOps operating models, container-era infrastructure, and production AI systems. Before AI became a product category, I was already building automated systems that had to reason, decide, and act under pressure. Today that experience is focused on one problem: making agentic AI shippable.

  • Took over and rebuilt several stalled AI platforms, getting them to market in weeks to a few months.
  • Helped move a generative-AI security product from research toward go-to-market readiness.
  • Built and led an agentic AI workflow platform through product buildout and acquisition.
  • Designed cloud operating models and automation practices for high-stakes enterprise environments.
  • Authored and implemented a pre-DevOps operating model in 2006, focused on automation, shared ownership, operational feedback loops, and reducing handoff failure.
  • Built early LXC-era container platform and service-mesh systems before Docker became mainstream.

Ready to make your agentic AI product shippable?

If the demo works but the product is not yet credible enough for customers, investors, or production, start with a Product Rescue Diagnostic.