AI Delivery Audit
Do the AI delivery audit before you build the custom agent
Why a paid audit prevents custom AI agents from becoming expensive prompt experiments.
By JirakJ
4 min read
Field notes
Weekly notes on AI delivery work.
Practical writing for founders, SaaS teams, agencies and operators building custom agents, prototypes, documentation systems and AI-assisted delivery workflows.
Prototype Sprint
A prototype is only useful if engineering can inherit it
How to design AI-assisted prototypes that do not collapse after the demo.
By JirakJ
5 min read
AI Operating Model
Private prompts are not a company process
The hidden cost of AI usage that lives inside personal chat histories.
By JirakJ
6 min read
Documentation
Documentation is delivery, not admin
Why documentation must be built into AI-assisted software delivery instead of cleaned up later.
By JirakJ
4 min read
Custom Agents
Name the agent owner before you hire the agent builder
A custom AI agent needs accountability before architecture.
By JirakJ
5 min read
Development Acceleration
AI-generated code needs delivery rules, not blind trust
How engineering teams can use AI coding tools without losing architecture and review discipline.
By JirakJ
6 min read
Product Specification
Use AI to sharpen specs, not replace product thinking
A practical way to use AI in product specification without outsourcing judgment.
By JirakJ
4 min read
Research Agents
Build competitor monitoring agents with human review built in
How to make AI competitor research useful without trusting summaries blindly.
By JirakJ
5 min read
Agent Operations
Every serious AI agent needs a failure path
The difference between a demo agent and an operated workflow is what happens when it fails.
By JirakJ
6 min read
Consulting
Fixed-price AI projects only work with sharp scope
Why premium AI consulting should sell defined outcomes instead of open-ended experimentation.
By JirakJ
4 min read
Founder Delivery
AI delivery streams for non-technical founders
How founders can turn an idea into a buildable workflow without pretending to be engineers.
By JirakJ
5 min read
Support Agents
Set the quality bar before building a support response agent
Support automation fails when nobody defines what a good answer looks like.
By JirakJ
6 min read
Documentation
Turn meeting notes into delivery decisions
AI summaries are not enough; teams need decisions, owners and next actions.
By JirakJ
4 min read
Workflow Design
Agentic workflows start with input design
Most agent failures begin before the model responds: with vague, inconsistent inputs.
By JirakJ
5 min read
AI Readiness
AI readiness is a delivery question
A company is ready for AI when its workflows, owners and data are clear enough to improve.
By JirakJ
6 min read
AI Strategy
AI roadmaps fail without an operating model
A list of AI ideas is not a plan until someone defines how work will move.
By JirakJ
4 min read
Internal Tools
Internal tools are the best place to prototype AI delivery
Why internal workflows are often safer and more valuable than customer-facing AI experiments.
By JirakJ
5 min read
Custom Agents
Build vs buy: when a custom AI agent makes sense
A practical filter for deciding whether to buy software, configure automation or build a custom agent.
By JirakJ
6 min read
Agent Operations
Agent dashboards are not monitoring
What teams should actually track when an AI agent runs inside a business workflow.
By JirakJ
4 min read
Documentation
How to scope an AI documentation pipeline
The minimum useful documentation pipeline for teams that ship fast and forget why.
By JirakJ
5 min read
Validation
Validate AI output like product work
AI validation should test usefulness, risk and fit, not just factual accuracy.
By JirakJ
6 min read
Prototype Sprint
What an AI prototype sprint should include
The deliverables that make a two-week AI prototype useful after the sprint ends.
By JirakJ
4 min read
Sales Operations
CRM enrichment agents need source discipline
How to avoid filling your CRM with confident but unverifiable AI-generated data.
By JirakJ
5 min read
Agency Delivery
AI for agencies should improve client delivery, not just content volume
Where agencies can use AI to make scopes, handoffs and delivery quality stronger.
By JirakJ
6 min read
Technical Specification
Technical specs need business context
Why AI-assisted technical planning fails when business rules are missing.
By JirakJ
4 min read
Security
AI agent security starts with scope
The safest AI agent is often the one with fewer permissions and a clearer job.
By JirakJ
5 min read
Implementation
From AI idea to implementation brief
A simple structure for converting an AI opportunity into something a team can estimate.
By JirakJ
6 min read
Testing
Testing belongs inside AI-assisted delivery
Why teams should define tests before using AI to generate implementation work.
By JirakJ
4 min read
Consulting
Why small AI engagements should still be paid
Free discovery creates vague advice; paid audits create usable decisions.
By JirakJ
5 min read
Reporting Agents
Report generation agents need editorial rules
How to make AI-generated reports useful without losing voice, structure or accountability.
By JirakJ
6 min read
Automation
Do you need a custom agent or just an automation script?
A practical distinction that saves budget and complexity.
By JirakJ
4 min read
Positioning
Founder-led AI consulting needs a sharper point of view
Why buyers respond to specific delivery thinking more than broad AI capability claims.
By JirakJ
5 min read
Measurement
AI delivery metrics that actually matter
Measure less hype and more throughput, quality, reuse and handoff strength.
By JirakJ
6 min read
Knowledge Agents
Do not build a knowledge-base agent before cleaning the knowledge
Retrieval does not fix messy source material; it exposes it.
By JirakJ
4 min read
Handoff
The AI project handoff checklist
What buyers should receive before an AI prototype, agent or workflow is considered done.
By JirakJ
5 min read
Workflow Design
AI workflows need examples more than instructions
Good examples make AI outputs more consistent and easier for humans to review.
By JirakJ
6 min read
Product Strategy
Where AI belongs in client portals
A grounded view of AI features that help client portals instead of cluttering them.
By JirakJ
4 min read
Custom Agents
Map data sources before building the custom agent
The data source map is the difference between a reliable agent and a guessing machine.
By JirakJ
5 min read
SaaS
AI delivery for SaaS teams should start near the roadmap
How SaaS companies can use AI to improve product delivery before adding flashy AI features.
By JirakJ
6 min read
Tooling
Map the workflow before choosing the AI tool
Tool selection gets easier when the work is already understood.
By JirakJ
4 min read
Agent Operations
Human escalation is a feature, not a failure
Why serious AI agents should know when to stop and ask for help.
By JirakJ
5 min read
AI Consulting
AI delivery stream vs generic AI consulting
The difference between advice about AI and a working system around delivery.
By JirakJ
6 min read
Sales Agents
Lead research agents need quality controls
How to automate lead research without polluting outbound with bad assumptions.
By JirakJ
4 min read
Agent Operations
AI agent maintenance is real work
Agents drift as products, policies and data change; maintenance must be part of the plan.
By JirakJ
5 min read
Founder Delivery
Use a prototype sprint to improve investor conversations
A good prototype helps investors see the product logic, not just the interface.
By JirakJ
6 min read
Operations
Set a review cadence for AI workflows
AI workflows need regular inspection because business context changes.
By JirakJ
4 min read
Human Aspect
AI does not fix unclear ownership
If nobody owns the workflow now, an AI agent will not magically create accountability.
By JirakJ
5 min read
Custom Agents
Acceptance criteria for a custom AI agent
What to define before deciding that a custom agent is ready to use.
By JirakJ
6 min read
Documentation
AI-assisted release notes should explain decisions
Release notes become more useful when they capture why changes happened, not only what changed.
By JirakJ
4 min read
Retainers
When an AI delivery partner retainer makes sense
The signs that a company needs ongoing AI delivery support instead of a one-off project.
By JirakJ
5 min read
Custom Agents
Scope the AI agent pilot smaller than feels comfortable
Why a narrow pilot produces better evidence than a broad agent experiment.
By JirakJ
6 min read
Knowledge Work
AI is only useful if operational memory improves
The best AI workflows make company knowledge easier to reuse.
By JirakJ
4 min read
Reporting Agents
Manual reporting is a strong AI workflow candidate
How to identify reporting workflows that are worth automating with AI support.
By JirakJ
5 min read
Project Governance
AI projects need a stop rule
A stop rule protects teams from endless experimentation without delivery evidence.
By JirakJ
6 min read
Recruiting Agents
Recruiting support agents need careful boundaries
Where AI can support recruiting workflows without making sensitive decisions for humans.
By JirakJ
4 min read
Prototype Sprint
The gap between AI prototype and production is mostly workflow
Why prototypes stall when ownership, validation and documentation are missing.
By JirakJ
5 min read
Founder Delivery
Founder-led companies need AI delivery, not AI noise
How founder-led teams can use AI without scattering attention across tools and experiments.
By JirakJ
6 min read
Agent Operations
AI agent logs should teach you how the workflow fails
Logging is not only debugging; it is how teams learn what to improve.
By JirakJ
4 min read
Product Delivery
AI-assisted backlog refinement needs product constraints
AI can organize backlog items, but only humans can set product trade-offs.
By JirakJ
5 min read
AI Operating Model
Delivery systems beat prompt libraries
Prompt libraries help, but they are not enough to make AI work repeatable.
By JirakJ
6 min read
Custom Agents
Write output standards before agent prompts
If you cannot describe a good output, you cannot judge whether the agent works.
By JirakJ
4 min read
Integrations
Design the integration workflow before touching the API
AI integrations fail when tool calls are designed before business states.
By JirakJ
5 min read
AI Delivery Audit
Red flags in an AI delivery audit
The signs that a workflow is not ready for automation yet.
By JirakJ
6 min read
Client Delivery
Client reporting is a delivery workflow, not a document
How AI can improve client reporting when the workflow is designed around decisions.
By JirakJ
4 min read
Agent Operations
What to do after the first AI agent works
The next step is not more agents; it is operating discipline.
By JirakJ
5 min read
Executive Reporting
What executives should see in an AI delivery stream
Executives need decisions, risk and leverage, not implementation noise.
By JirakJ
6 min read
Workflow Design
AI workflows need non-goals
Defining what the workflow will not do is one of the fastest ways to make it safer.
By JirakJ
4 min read
Software Teams
AI delivery for small software teams
Small teams get leverage from AI when it reduces coordination and documentation drag.
By JirakJ
5 min read
Handoff
Handing a custom AI agent to an internal team
What must be true before an internal team can safely own a custom agent.
By JirakJ
6 min read
AI Delivery Audit
How to choose the first AI workflow to build
A practical filter for choosing the first workflow that deserves AI support.
By JirakJ
4 min read
Human Aspect
AI delivery needs taste
Taste is the human ability to know when output is technically correct but strategically wrong.
By JirakJ
5 min read
Operations
Run a weekly AI delivery review
A lightweight weekly review can keep AI workflows useful, safe and tied to delivery.
By JirakJ
6 min read