Hands-on AI anti-consulting for real systems under pressure
Your AI isn't failing because of strategy decks. It's failing because real systems are messy. We step into live codebases, debug production issues, and help teams regain control over quality, cost, and reliability.
Common Reasons Teams Hire Me
Quality is bad
The system exists but outputs are inconsistent or wrong
Costs are too high
API bills spiraling, usage growing faster than value
Trust is gone
Users or stakeholders don't trust AI outputs anymore
Security concerns
InfoSec or legal has blockers you can't resolve
Team disagreement
Engineers are split on approach and need arbitration
Black box anxiety
Nobody understands why it does what it does
The First Week
No slow ramp-up. We get into the system immediately and start identifying what's actually broken.
- Read the system: code, prompts, data, logs
- Identify the top 3 failure points
- Propose a short plan with priorities
- Start fixing the highest-leverage piece
- Document findings for the team
Retrieval and knowledge systems
RAG, embeddings, search quality
Tool calling and agent design
Reliability, error handling, orchestration
Evaluation harnesses
Automated quality measurement
Prompting and output control
Consistency, formatting, guardrails
Deployment and monitoring
Observability, alerting, debugging
Team training
Level up while building
This is for you if...
Perfect fit
- You have an AI system in production that's not performing well
- Costs are spiraling and you don't know why
- Nobody trusts the AI outputs anymore
- Security or legal has concerns you can't address
- Your team is stuck and needs an outside perspective
- You need someone who can both diagnose and fix
Not the best fit
- You need strategic planning, not hands-on help (see Strategy)
- You want a full implementation team (see Implementation)
Concrete Outcomes
No vague promises. Here's what actually changes.
Problem Identified
Clear understanding of why things aren't working, with evidence and root causes, not guesses.
Root cause analysis, failure mode catalog, fix priority list
Quick Wins Shipped
The highest-leverage fixes implemented, not just recommended. Results you can measure.
Specific metrics improved (quality, cost, latency)
Team Leveled Up
Your engineers learn while we fix together. They can handle the next problem.
Knowledge transfer, documented patterns, reduced future escalations
How We Work Together
A clear, step-by-step approach so you know exactly what to expect.
System Assessment
Deep dive into your existing system. Code, prompts, data flows, failure logs. Understand what you actually have.
Assessment report + priority issues
Access to systems + 2-3 walkthrough sessions
Quick Wins
Fix the highest-leverage problems first. Usually there are easy wins hiding in the weeds.
Implemented fixes + before/after metrics
Code review access + testing environment
Systematic Improvement
Work through the deeper issues. Architecture changes, evaluation setup, monitoring improvements.
System improvements + documentation
Regular syncs + decision making
Knowledge Transfer
Teach your team what we learned. They should be able to handle the next problem.
Training sessions + runbooks
Team participation in sessions
Ways to Work Together
Choose the engagement model that fits your needs and timeline.
Office Hours Retainer
- Scheduled consulting hours
- Priority async support
- Architecture reviews
- Team coaching access
Embedded Consultant
- Regular hands-on sessions
- Pair programming time
- Team training integrated
- Ongoing problem solving
Fix-It Sprint
- Rapid assessment
- High-priority fixes
- Stabilization work
- Handover documentation
Want the real lessons from production AI?
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