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Update CLAUDE.md with content strategy, voice guide, and 30-day plan context Adds author background, tone/style guidelines, the active 30-day series arc structure, and approved tag/category conventions so AI assistants maintain consistency when creating new posts. https://claude.ai/code/session_01Nfbjr497RyUJTqFxh2VM8d
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‎CLAUDE.md‎

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Personal blog/portfolio for Akash Talole, built with **Jekyll** and the **Chirpy theme** (~7.5), hosted on **GitHub Pages** at `https://akashtalole.github.io`.
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- **Content focus**: AI/ML topics (GenAI, Claude Code, GitHub Copilot, Agentic AI, SDLC)
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- **Author**: Akash Talole — Lead AI Engineer, 11 years of industry experience
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- **Content focus**: Practical AI engineering — Claude Code, GitHub Copilot, Microsoft Copilot Studio, Agentic AI, Coding Agents, Agent Skills, Claude CoWork, AI in SDLC
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- **Deployment**: GitHub Actions builds the site and deploys to GitHub Pages on push to `main`/`master`
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## Content Strategy & Voice
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### Author Background
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Akash is a Lead AI Engineer with 11 years of experience. Posts are written from the perspective of someone actively using these tools on real enterprise projects — not reviewing them from the outside.
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### Tone & Style
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- **Humanized, direct, no-fluff** — write like a senior engineer explaining something to a peer, not a tutorial site
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- **Practical over theoretical** — lead with real use cases, real friction, real outcomes
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- **Honest** — acknowledge limitations and failure modes; don't oversell tools
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- **Audience**: engineers who already code for a living and are past "should I try AI?" — they're in the "how do I use this well?" phase
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- Avoid: marketing language, excessive disclaimers, generic intros, bullet-point padding
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### Active Content Series: 30-Day AI Engineering Plan
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A pinned series (`_posts/2026-04-09-30-day-ai-engineering-blog-plan.md`) maps out 30 daily posts across five arcs. **Before creating any new post, check this plan to avoid duplicates and maintain arc continuity.**
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| Arc | Days | Theme |
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|-----|------|-------|
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| 1 | 1–6 | Foundations & the AI-Augmented Engineer |
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| 2 | 7–13 | Claude Code for Enterprise |
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| 3 | 14–19 | GitHub Copilot Mastery |
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| 4 | 20–25 | Coding Agents & Agent Skills |
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| 5 | 26–30 | Microsoft Copilot Studio & Multi-Agent Solutions |
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### Approved Tags & Categories
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Use these consistently — do not invent new tags without a clear reason:
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| Topic | Category | Tags |
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|-------|----------|------|
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| Claude Code | `ai`, `claude-code` | `claude-code`, `enterprise`, `coding-agents` |
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| Claude CoWork | `ai`, `claude-code` | `claude-cowork`, `pair-programming` |
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| GitHub Copilot | `ai`, `github-copilot` | `github-copilot`, `copilot-workspace` |
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| Copilot Studio | `ai`, `copilot-studio` | `copilot-studio`, `multi-agent`, `microsoft` |
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| Agentic AI | `ai`, `agentic-ai` | `agentic-ai`, `agents` |
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| Agent Skills | `ai`, `agent-skills` | `agent-skills`, `tool-use` |
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| AI in SDLC | `ai`, `sdlc` | `sdlc`, `ai-in-sdlc` |
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| Coding Agents | `ai`, `coding-agents` | `coding-agents`, `automation` |
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| Meta / Series | `ai`, `meta` | `meta` |
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---
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## Creating Blog Posts
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### File Naming

‎README.md‎

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# Akash Talole — AI Blog
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A personal space where I share what I'm actually learning, building, and breaking with AI tools — not just theory, but real hands-on experiments and honest takes.
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If you've ever wondered how far you can push agentic AI in your day-to-day workflow, or whether GitHub Copilot and Claude Code can genuinely change the way you write software, this blog is for you. I cover things I wish someone had written down when I was figuring them out.
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## What You'll Find Here
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- **Agentic AI** — how autonomous agents work in practice, where they shine, and where they still fall flat
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- **Claude Code** — tips, workflows, and real use cases for using Claude as a coding companion
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- **Claude CoWork** — experiments with collaborative AI-assisted development
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- **GitHub Copilot** — practical tricks beyond autocomplete, and how to get the most out of it
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- **Microsoft Copilot Studio** — building custom copilots without getting lost in the docs
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- **AI in SDLC** — where AI actually fits into the software development lifecycle (and where it doesn't)
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- **More** — anything else I find genuinely useful, interesting, or worth talking about in the AI/ML space
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No fluff, no hype — just practical stuff from someone who spends a lot of time experimenting with these tools and wants to share what actually works.
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---
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# Chirpy Starter
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[![Gem Version](https://img.shields.io/gem/v/jekyll-theme-chirpy)][gem] 

‎_posts/2026-04-09-30-day-ai-engineering-blog-plan.md‎

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---
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layout: post
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title: "30 Days of AI Engineering — My Content Plan as a Lead AI Engineer"
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date: 2026-04-09 08:00:00 +0530
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categories: [ai, meta]
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tags: [ai, claude-code, github-copilot, copilot-studio, agentic-ai, agent-skills, sdlc, coding-agents]
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description: "A structured 30-day blog roadmap covering Claude Code, GitHub Copilot, Microsoft Copilot Studio, agentic AI, coding agents, and AI in SDLC — from a Lead AI Engineer with 11 years of experience."
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author: akashtalole
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pin: true
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---
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Eleven years into this industry, and I'll be honest — the last 18 months have been more disruptive to how I work than the previous decade combined. Not in a scary way. In a "I need to document all of this before I forget what it was like before" kind of way.
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This is that documentation project.
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Over the next 30 days I'm publishing one post a day covering the AI tools and workflows I'm actively using on the job right now: Claude Code for enterprise teams, GitHub Copilot beyond the basics, Microsoft Copilot Studio multi-agent solutions, coding agents, agent skills, AI in the SDLC, and everything in between.
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Not tutorials copied from docs. Real stuff, with real friction, real decisions, and real outcomes.
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Here's the full plan.
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---
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## The 30-Day Roadmap
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I've split this into five thematic arcs so each week builds on the last. Reading them in order makes sense, but each post is also designed to stand on its own.
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---
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### Arc 1 — Foundations & the AI-Augmented Engineer (Days 1–6)
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Before diving into any specific tool, I want to set context. These posts are about the mindset, the landscape, and how I actually think about AI in my day-to-day work as a Lead AI Engineer.
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| Day | Title | What It Covers |
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|-----|-------|----------------|
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| 1 | **Why I'm Writing 30 Days of AI Engineering** | The "why" behind this series — what's changed, why now, and what I want to figure out by the end |
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| 2 | **AI in the SDLC — The Honest State of Things in 2026** | Where AI genuinely fits in the software development lifecycle today vs. where the hype says it fits |
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| 3 | **The Agentic AI Mental Model Every Engineer Needs** | What "agentic" actually means in practice, why it matters, and how it changes the way you design systems |
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| 4 | **Agent Skills 101 — Building Blocks of Useful AI Agents** | Anatomy of a well-designed agent skill: inputs, outputs, tool use, memory, and failure modes |
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| 5 | **Choosing Your AI Toolchain — Claude Code, Copilot, or Copilot Studio?** | They're not competing — they solve different problems. Here's how I think about which to reach for |
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| 6 | **11 Years In, AI-Augmented — How My Workflow Actually Changed** | Honest before/after on what AI has changed in how I plan, code, review, and ship |
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---
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### Arc 2 — Claude Code for Enterprise (Days 7–13)
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This arc goes deep on Claude Code — not the getting-started guide, but the harder questions: how do you use it at scale, in enterprise environments, with real security and governance constraints?
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| Day | Title | What It Covers |
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|-----|-------|----------------|
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| 7 | **Setting Up Claude Code for Enterprise Teams** | Auth, security posture, rate limits, audit trails — what you need to figure out before rolling it out |
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| 8 | **Claude Code for Legacy Code Modernization** | Using Claude Code to understand, refactor, and document codebases you didn't write and barely understand |
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| 9 | **Claude CoWork — Async AI Pair Programming in Practice** | What Claude CoWork is, how it differs from standard Claude Code usage, and when it's genuinely useful |
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| 10 | **Prompt Engineering for Coding Tasks — What Actually Works** | The prompt patterns I've found most reliable for code generation, review, and explanation in real projects |
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| 11 | **Claude Code for Code Reviews at Scale** | Using Claude Code as a pre-reviewer: what it catches, what it misses, and how to trust it the right amount |
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| 12 | **Integrating Claude Code into CI/CD Pipelines** | Automated code quality, PR summaries, test suggestions — practical integration patterns I've tried |
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| 13 | **Claude Code in Regulated Environments — A Security-First Look** | Data residency, prompt injection risks, tool access controls — what enterprise security teams will ask you |
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---
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### Arc 3 — GitHub Copilot Mastery (Days 14–19)
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GitHub Copilot is probably the tool most engineers have tried and feel like they've figured out. They haven't. This arc is about going past autocomplete.
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| Day | Title | What It Covers |
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|-----|-------|----------------|
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| 14 | **GitHub Copilot Beyond Autocomplete — The Features Most People Miss** | Copilot Chat, inline fixes, `/explain`, `/tests`, slash commands in the terminal — the full picture |
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| 15 | **Writing Better Prompts for GitHub Copilot in VS Code** | Comment-driven development, naming conventions, and context tricks that dramatically improve output quality |
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| 16 | **GitHub Copilot for Test Generation — Does It Actually Work?** | Honest evaluation: where Copilot-generated tests are good, where they're dangerous, and how to use them safely |
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| 17 | **Copilot for PR Descriptions, Docs, and Commit Messages** | The non-code uses of Copilot that save real time if you know how to set them up |
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| 18 | **Copilot Workspace — Hands-On with Agentic GitHub Copilot** | What Copilot Workspace is, how it approaches multi-step tasks, and where it fits vs. Claude Code |
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| 19 | **GitHub Copilot in Enterprise Governance Frameworks** | Policy controls, content exclusions, audit logs, and how to get security/compliance teams comfortable with it |
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---
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### Arc 4 — Coding Agents & Agent Skills (Days 20–25)
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This is the arc I'm most excited about. Coding agents are still early, but they're already changing how certain classes of engineering work get done. This is where I share what I've actually built and learned.
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| Day | Title | What It Covers |
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| 20 | **What Makes a Good Coding Agent — Design Principles** | Scope, tool access, failure recovery, human-in-the-loop checkpoints — the design decisions that matter most |
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| 21 | **Building Your First Coding Agent — A Practical Walkthrough** | Hands-on: building a simple but real coding agent, step by step, with the decisions explained |
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| 22 | **Tool Use in AI Agents — Patterns That Work in Production** | Function calling, tool chaining, error handling, and the patterns I've found reliable vs. brittle |
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| 23 | **Agent Memory and Context Management — The Hard Part** | Short-term vs. long-term memory, context window strategies, and how agents lose the thread (and how to prevent it) |
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| 24 | **Multi-Step Coding Agents — Patterns and Failure Modes** | What happens when you chain multiple agent actions, where things break, and how to design for recovery |
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| 25 | **Evaluating Coding Agent Quality — Beyond "Did It Run?"** | How to actually measure whether an agent is doing the right thing: evals, tracing, human review workflows |
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### Arc 5 — Microsoft Copilot Studio & Multi-Agent Solutions (Days 26–30)
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The final arc covers the multi-agent work I'm doing right now in Microsoft Copilot Studio — designing, building, and operating agents that work together to solve enterprise-scale problems.
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| Day | Title | What It Covers |
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|-----|-------|----------------|
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| 26 | **Microsoft Copilot Studio for Developers — What You Need to Know** | The honest developer's guide: what Copilot Studio is good at, where it falls short, and how to think about it |
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| 27 | **Designing Multi-Agent Workflows in Copilot Studio** | Architecture patterns for multi-agent systems: orchestration vs. choreography, handoff design, shared context |
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| 28 | **Connecting Copilot Studio Agents to Enterprise Systems** | Connectors, custom APIs, authentication, and the integration patterns that hold up under real load |
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| 29 | **Multi-Agent Debugging and Observability — Staying Sane** | Tracing agent conversations, surfacing failures, and building visibility into systems that are hard to inspect |
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| 30 | **30 Days Done — What I Learned, What Changed, What's Next** | Synthesis post: the biggest surprises, what I'd do differently, and where I think all of this is heading |
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---
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## A Few Things I Want to Be Upfront About
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This isn't a sponsored series. I use all of these tools professionally and pay for most of them personally. When something doesn't work well, I'll say so.
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I'm also not writing for beginners. These posts assume you write code for a living, you've at least heard of most of these tools, and you're past the "should I try AI?" question. You're in the "how do I actually use this well?" phase. That's who I'm writing for.
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If a post doesn't land or you want me to go deeper on something, tell me. I'd rather adjust the plan mid-stream than finish 30 days of posts nobody found useful.
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Let's go.
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*Follow along via [RSS](/feed.xml) or bookmark this post — I'll keep it updated as the series progresses.*

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