@cheneypiano I haven't noticed any differences vs a cloud model (but my 90%++ use case is communicating with LLMs, which wouldn't mind the occasional typo anyway)
Late 2024: AI agencies sold n8n workflows for $2-$5K.
Mid 2025: they pivoted to AI agents for $5-15K.
Today: Claude Code ships in hours what used to take weeks, and most agencies are still pitching 2024's playbook.
I spent 2 months rewriting mine for where we actually are in April 2026.
Inside:
→ The offer closing $25K-$60K projects right now
→ Top 5 industries worth selling to this quarter
→ Content schedule generating my inbound (exact post types + cadence)
→ LinkedIn + cold email sequences booking calls today → My 4-call sales process from first touch to signed
→ The strategy doc + proposal template I'm using to close
→ 3 live client builds my team is shipping this quarter
BONUS: First 100 people also get 2 discovery call recordings from my own sales process.
Like + RT + reply PLAYBOOK and I'll DM you the link. Make sure to follow me so I can DM you.
I mapped every AI automation opportunity across 25 industries.
10-15 pain points each. With the exact positioning, pricing range, and who to sell to.
This took me 4 years and 80+ client engagements to figure out.
A lot of AI agencies pick a niche and pray.
They don't know the actual pain points.
They don't know who the buyer is.
They don't know what these companies are already paying for broken solutions.
They don't know what the realistic project size is.
So they end up competing on price for generic "AI automation" gigs.
I've worked with marketing agencies, recruiting firms, e-commerce brands, law firms, real estate companies, healthcare practices, financial services, SaaS companies, manufacturing, construction, logistics, and more.
Every single one has 10-15 processes that are bleeding money because they're still done manually.
Here's what the guide covers for each industry:
→ The top 10-15 automation pain points (ranked by ROI)
→ Who the actual buyer is (CEO, COO, ops manager, etc.)
→ What they're currently paying for manual labor or broken SaaS
→ Realistic project pricing ($5K-$60K+ depending on scope)
→ The discovery questions that unlock the deal
→ How to position yourself as the expert even if you've never worked in that industry
→ Red flags to avoid (industries and company sizes that aren't worth it)
25 industries and 300+ specific automation opportunities.
This is the cheat code for picking your niche and knowing exactly what to sell before you ever get on a call.
Like + RT + reply "NICHE" and I'll send you the full guide (Must be following so I can DM)
@trq212 Please expose limit data Claude Code CLI so devs can build actual guardrails instead of hitting a hard stop mid-session. GitHub issue #32796 tracks this.
The rate_limits field (5hr/7day used_percentage) already exists in statusline scripts — the data is there.🙏
@AndrewWarner@aperezDeFi@calebhodges If you have any small/medium software concepts on your backlog @AndrewWarner let me know and we can build one of them together and I'll show you how it works. SaaS, AI, Desktop, even an internal tool or script - anything will work
@AndrewWarner@aperezDeFi@calebhodges Thanks @AndrewWarner !
Currently all of the monitoring is post project completion, but the output of this analysis (tighter prompts, more LLM friendly task decomposition, cleaner directions to finding files or tools..) feeds into the next project so the cycle is always evolving
@AndrewWarner@aperezDeFi@calebhodges I have a dedicated efficiency agent that monitors any heavy LLM usage. In this example (a software development "sprint") you can see the costs being driven down from $3.92 to $2.37 per task. (it was initially over $20/task)
@trentjhughes@CoFoundersNik Thank you for making me feel OK about having 3 books going at any given time. I bucket them into categories and read based on mood (and how much is in the mental tank):
- Business / Financial / Growth
- Technical / Scientific
- Fiction