Consulting offer
AI coding agent onboarding for engineering teams—scoped, reviewable, and shippable
For VP Engineering, Heads of Platform, and CTOs at B2B SaaS companies (roughly 20-200 engineers) deploying AI coding agents and secure autonomous workflows.
Konuke helps you turn agent assistance into a delivery practice: predictable PRs, clear ownership, and guardrails that security and leads can defend.
What you get (concretely)
- AI coding agent SDLC map (human vs. agent ownership)
- PR + review checklist tuned to your risk profile
- Starter templates for specs, tests, and rollout communications
- Security/privacy notes aligned to your stack (not generic slogans)
- Office hours or async review window (scoped in the SOW)
Recent engagements
Real teams shipping with agents — without losing control
Anonymized snapshots from the last 12 months. We’re happy to share more context (including metrics and process) on a fit call.
B2B SaaS platform
80 engineersDefined AI coding agent PR workflow and review checklist. Cut oversized diffs and restored reviewer confidence across the team in under three weeks.
Fintech infrastructure
Platform teamMapped data boundaries and secrets handling for coding assistants and CI agents. Security approved a phased rollout tied to existing audit trails.
Series B product company
Product engineeringRan a two-week onboarding intensive with shared prompt templates, ownership model, and metrics focused on quality—not token volume.
B2B SaaS (platform team)
45 engineersEmbedded the PR review checklist + Task Delegation Scorecard into their process. Reviewer turnaround on agent PRs dropped from 3+ days to same-day.
First two weeks (typical)
Week 0 — Fit call
30 minutes: stakeholders, constraints, success criteria, and whether an intensive or embedded model fits.
Week 1 — Map the system
Tool inventory, data boundaries, PR/review reality, and where agents should (and should not) touch production paths.
Week 2 — Ship the first playbook
Templates + checklists your team can run without us: PR norms, prompt/tool versioning, and a lightweight metrics set.
Pricing and packaging
Engagements typically start at $12k for a focused two-week intensive.
Exact statements of work depend on team size, regulated industry constraints, and whether you need embedded support versus a time-boxed intensive. The fit call is how we de-risk scope for both sides.
Engagement modules
Most teams mix one intensive with follow-on reviews. We will recommend a lane after we understand your repo reality—not your slide deck aspirations.
AI onboarding intensive
A structured week for leads and ICs: toolchains, prompting discipline, code review with agents, and a delivery backlog you can execute.
- Role maps: where agents help vs. where humans decide
- Branching and PR habits that keep diffs reviewable
- Starter templates for specs, tests, and rollout checklists
Operating model design
Translate “we tried Copilot” into a practice: ownership, SLAs for agent-assisted work, and metrics that reflect quality—not just volume.
- RACI for human/agent steps across the SDLC
- Lightweight eval hooks for prompts and tools
- Change management for skeptical stakeholders
Architecture & risk review
Align agents with your threat model: data residency, secrets, third-party tools, and safe automation boundaries.
- Data flow maps for AI features and integrations
- Secrets and key hygiene for agent runtimes
- Incident runbooks when automation misfires
Objections we expect (and address)
▸We tried Copilot and it did not stick.
Most rollouts fail on norms, not tooling. We anchor on PR/review habits, bounded tasks, and metrics your leads already trust—so the practice survives the first busy quarter.
▸Security/legal will not let us “send code to AI.”
We start with data classification and realistic tool modes (local vs. cloud), then propose phased paths that match your audit story—no hand-wavy “just disable it.”
▸We only have budget for training.
Training without templates becomes theater. Deliverables are concrete artifacts (checklists, maps, comms drafts) your team runs next week—not slides you file away.
▸We need this across multiple teams.
We scope a pilot lane first (one product area or platform team), prove the operating model, then reuse the playbook for wider rollout with your internal champions.
Next step
Book a fit call—or send context async if calendars are messy this week.