@akshay_pachaar: 95% of enterprise AI projects fail to deliver. but rarely because the model is bad. they fail because teams can’t answe…

95% of enterprise AI projects fail to deliver.

but rarely because the model is bad.

they fail because teams can’t answer the harder questions:

• how do we govern this?
• how do we prove ROI?
• how do we deploy it safely in regulated environments?
• how do we move beyond experiments into real systems?

someone who has spent 7 years working on Fortune 500 and government AI deployments turned those lessons into a free book.

AI Strategy Blueprint covers:

• the 10-20-70 rule for AI investment
• practical governance frameworks
• ROI methods finance teams can actually trust
• deployment patterns for regulated and air-gapped environments
• a roadmap from early experiments to scaled adoption
• case studies from real deployments

through our partnership with Iternal Technologies, you can get the full book for free, either as a PDF or Kindle version.

link in the next tweet. (limited time offer)

download it here:

The top Claude Code CLI integrations to give you superpowers:

1. GitHub

The repo stops being a folder of files and becomes something the agent actually runs.

It reads and writes issues, PRs, Actions, and releases, so it works the codebase the way an engineer does, not by editing text on disk.

This is the gap between an agent that touches code and one that actually ships it.

2. HuggingFace

This is where your models and datasets live, and the agent can reach all of it.

It pulls a base model, runs the training, and pushes the fine-tuned version back, without you ever leaving the terminal.

The whole loop happens in one place.

3. Bright Data

Web access that actually works for an agent, instead of a scraper you have to babysit.

It pulls live search, full pages, and clean data from sites that normally block bots, and now it can even build custom scrapers from the terminal.

Collect data from any website by turning prompts into ready-to-run scrapers with built-in proxies and automatic unblocking.

GitHub: https://github.com/brightdata/cli

(don’t forget to star )

4. Stripe

Payments without ever opening the dashboard.

It forwards live webhooks and fires real payment events, so the agent runs through the whole checkout instead of faking it.

The only real way to know your billing works is to run actual money through it.

5. InsForge

A full backend in one CLI.

Database, auth, storage, edge functions, hosting, and an AI gateway, all in one place instead of stitching five services together. The agent sets up the infrastructure the way a backend engineer would.

Think of it as a backend built for agents.

GitHub: https://github.com/InsForge/insforge…

(don’t forget to star )

6. CodeRabbit

It reviews the agent’s own code before you ever see it.

It catches bugs, security holes, and sloppy patterns while the change is still local, so nothing messy makes it into a PR.

An agent that checks its own work first is a very different teammate.

7. Playwright

It gives the agent hands in a real browser.

Click, fill forms, take screenshots, and run UI tests across Chrome, Firefox, and Safari, on the real page instead of guessing from the HTML.

Easily the most underrated way to let an agent check what it built.

8. Google Workspace

Gmail, Drive, Calendar, Sheets, and Docs through one connector.

It is built on Google’s own APIs and made for agents to actually do the work, not just read it, so it can draft the reply, update the sheet, and block off the calendar in one go.

An agent that can read your inbox but can’t act on it is only half useful.

9. Slack

It puts the agent right where your team already works.

It builds and runs workflows that post updates and sort through channels, so “tell me what I missed in # incidents and flag anything urgent” just happens without you switching tabs.

This is the one that makes the agent feel present instead of stuck in a terminal.

10. E2B

A safe sandbox for code the agent wrote itself.

It spins up a small isolated VM, runs the code, grabs the output, then shuts the whole thing down.

This is what lets you actually let the agent run what it writes.

GitHub: https://github.com/e2b-dev/E2B

(don’t forget to star )

11. Unsloth

Fast local fine-tuning without the cloud bill.

It trains LoRA and QLoRA adapters about 2x faster on a lot less VRAM, then exports to GGUF or pushes straight to the hub.

This is what turns fine-tuning from a whole project into just another step.

GitHub: https://github.com/unslothai/unsloth…

(don’t forget to star )

12. ffmpeg

The media tool that does almost everything, now in the agent’s hands.

Cut, convert, and pull audio or video out of just about anything in a single command.

Old, unglamorous, and still the thing every media pipeline quietly runs on.

That said, if you want to see how this whole stack fits together, I wrote a full deep dive on how Claude Code’s harness works, what actually goes in the .claude/ folder, and how hooks, skills, and subagents come together into a real workflow.

The article is quoted below.