Imraan
71 posts
Claude Code weekly limits are increasing 50%, now through July 13.
Live now for all Pro, Max, Team, and seat-based Enterprise users.
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@JamesonCamp completely agree, staying fluid is literally the moat.
thats what I tell all the businesses we work with. You wanna be polyaimorous
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The wave is here but what’s wrong with this, and the OpenAI JV, and the anthropic one
Is DEEEEEP vendor lock. You do not want to be stuck using one companies models forever at this point
I like to say we are model agnostic when it comes to client work
We use what is best and can be changed
I’m also convinced that in the future, many companies will be using local models at much more affordable rates
If you’re looking to get your company AI native without being locked into one vendor forever
We’re here to help
First Squawk@FirstSquawk
GOOGLE TO RECRUIT HUNDREDS OF ENGINEERS TO ASSIST CLIENTS IN EMBRACING ITS AI – THE INFORMATION
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@lukepierceops anyone selling the 'how to' is usually not actually doing. happy to be proven wrong
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The gap I called out yesterday isn’t theoretical.
OpenAI’s deployment company is the proof of how big it is.
I’ve watched 18 people close their first AI implementation client in the last 8 weeks.
Working the exact market that sits underneath what OpenAI is chasing.
The $2M to $50M companies that need this just as badly.
Starting Monday I’m running a FREE 7-Day Challenge to show you exactly how they did it.
Same playbook and system. You’d be working directly with me and my team.
DM me “CHALLENGE” and I’ll send you the signup link.
Luke Pierce@lukepierceops
OpenAI just launched a deployment company with 19 consulting firms attached. AKA an Ai Implementation Agency but at a larger scale. None of them are taking calls from a $5M agency. Every founder I’ve talked to the last 4 weeks is doing $2M to $30M. They have the same problem the enterprise has. Manual ops, broken workflows, 20 tools that don’t talk. The difference is they can’t afford a 6 month enterprise engagement and 14 stakeholders signing off. That’s the gap and it’s bigger than the enterprise market they’re chasing.
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@ClaudeDevs tell me youre worried about codex without telling me youre worried about codex
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Starting June 15, paid Claude plans can claim a dedicated monthly credit for programmatic usage.
The credit covers usage of:
- Claude Agent SDK
- claude -p
- Claude Code GitHub Actions
- Third-party apps built on the Agent SDK
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@alliekmiller completely agree, choosing where to point the FDE and building for desired outcome is the skill.
that takes someone orchestrating the FDE and typically wont come from within the org itself
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The most expensive mistake in enterprise AI right now: treating FDEs as your whole transformation plan.
Forward deployed engineers (FDEs) are important for custom deployments, but they won’t fix the change management issue most enterprises are facing.
It’s likely more the former that Anthropic and OpenAI will continue to prioritize (and hire into the thousands, who knows). Beyond performance and cost, it’s systems integration, ROI, and literal usefulness that drive revenue and stickiness.
*However*
External FDEs, in my opinion, will not make your company an AI-first company.
You can have the sleekest multi-agent orchestrations and still have the majority of your employee base hating AI, avoiding AI, and distrusting leadership decisions on AI.
And we already know this because we see this in traditional SaaS too: you can customize the heck out of your Salesforce deployment, but that doesn’t mean your sales team will improve their data hygiene or even attempt to change the way they track and grow with it.
Buying a fancier car doesn’t mean you magically learn to drive better overnight.
If you’re an enterprise exec and FDEs are sold as the immediate and sole solution to your company transformation woes, walk away.
It’s the combination of tech *and* people enablement *and* process reinvention that compounds into actual business outcomes.
Large complex enterprises will stall out if they only prioritize the first.
Aaron Levie@levie
Forward deployed engineers, or equivalent, are about to become one of the most in-demand jobs in tech. And one of the most important functions for AI rollouts. Deploying agents is far more technical of a task than most people realize, often far more involved than deploying software. Software generally works the same way every time, and generally for the past few decades has been updated versions of an existing technology or concept (which basically means easier for the enterprise to update their workflows on a newer system). With agents, you’re actually deploying the equivalent of work output within the enterprise. The customer is effectively using you as a professional services provider for a task, which they expect to get solved nearly end-to-end now. This means you need to actually deeply understand the business process as a vendor, and get the customer from the current to the end state seamlessly. Companies need help figuring out which models will work best for their workflows, they need extensive evals setup often, they need change management support for workflows, they need to get their data setup for the agents, and constant tuning of the agentic system for their process. Massive role in tech now. And another example of the kind of highly technical work that AI is creating.
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@hasantoxr you get nerfed not posting from within the platforms directly
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Holy shit... someone made it work that I can integrate a social media manager inside Claude
It's called OmniSocials and it lets Claude draft, schedule, and publish to 10 platforms from a single command.
No Hootsuite. No Buffer. No $200/seat pricing.
Here's everything you need to know: 👇
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@thatguybg i dont think they will need a platform, youre still thinking like a human imo
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the largest company of the AI revollution (and likely all time) will be a platform for agents and generative apps
this platform has not yet been built
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the best decision I made this year was to connect my entire business to claude
the tech stack that makes it possible:
> linear: we use this for project and product management. used to be just for PMs, designers, and engineers. now everyone on the support team has access via MCP
> unblocked: added it to slack and it gathers context of every conversation happening there. connected to github so it understands our code. connected to Linear so it knows what engineers are building. it has a full 360 of the business.
> fellow: records every single meeting with full transcriptions and summaries.
> claude: ties it all together. for almost all queries, I just go straight to claude.
for example, last week, I asked claude: "what's the status of the podcast feature rollout?"
it read the engineering slack channel, pulled the relevant linear tickets, checked which PRs had merged, read through all the relevant meeting transcripts, and gave me a status update with timeline + blockers in 30 seconds
I would have easily spent a couple hours doing that manually
there's just so much transparency through the business by connecting all of these different applications through claude
if anything ever goes sideways (a spike in support tickets, a regression, a customer issue) I can just ask claude what's going on and it picks up context from a slack channel I don't even have access to, surfaces the ticket that was created, tells me which engineer is working on it and when it's shipping.
unfathomably exciting time to build dope shit
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This is a business in a box.
Claude just made it possible to build and deploy AI agents at scale with managed infrastructure.
Here's how to sell it:
1. Pick a niche (real estate, e-com, coaching, agencies)
2. Build one agent that solves their #1 repetitive problem
3. Deploy it on Claude's managed platform (they handle the infrastructure)
4. Charge $1,500-3,000 setup + $500/month per client
5. The agent runs 24/7. You maintain it for an hour a month.
10 clients = $5,000/month recurring before you even think about scaling.
The "prototype to launch in days" part is key. You can have a client's agent live before the second sales call.
Claude@claudeai
Introducing Claude Managed Agents: everything you need to build and deploy agents at scale. It pairs an agent harness tuned for performance with production infrastructure, so you can go from prototype to launch in days. Now in public beta on the Claude Platform.
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@timwangyc @seedtosunflower @Joshuabrowder congrats on the launch - genuine q whats the difference between this and existing solutions ?
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Introducing Ponder: the agentic video editor.
It’s a new paradigm for filmmaking, where powerful creative agents and humans collaborate to tell world-class stories.
We're also announcing our $2.5M pre-seed, led by Liu Jiang from Sunflower (@seedtosunflower), with @Joshuabrowder and @MattHartman.
Joined by @levie (Box), @emerywells (Frame), @JaredLeto, @CommaCapital, the @nyuniversity venture fund, @cory, @darian314, @shiffman, and many more incredible founders, investors, and creators.
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This is good but can be expanded a lot further. If one has exact output that it needs. Content creation, code/app, ... anything bigger/that takes multiple steps. It can be done in similar fashion but with custom flow that has multiple skills and agents. What should be taken from here is the principle of AI planning, executing, checking it own output, iterating on it's own critiuqe and chekcing again...
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/goal is f*cking insane.
You can literally get your AI agents to work for HOURS without manual intervention.
Already active in Claude Code and Codex - you need to use it now.
Use this prompt and your agents will complete any task on autopilot:
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@ZainManji seeing the exact same here in Dubai, also seeing a massive gap between what founders/operators think they need vs what will actually move the needle for their biz
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We've shipped 40+ AI engagements and have led FDE efforts in the last 12 months... here's the actual AI problems we've been solving for enterprises
1. Compressing long, multi-system business processes. Mapping a process that lives across email, Excel, SharePoint, ERPs, and DAMs, then collapsing it with agentic workflows.
2. Document and unstructured data extraction. Pulling structured data out of messy inputs at scale.
3. Internal knowledge and search across fragmented systems. Querying institutional knowledge that lives in calls, memos, CRM, and docs.
4. Customer-facing AI agents (chat, voice, support). Production agents handling end-customer interactions.
5. Agentic commerce. Catalogs, checkouts, and brand surfaces ready for AI agent traffic.
6. Computer vision in physical workflows and applied to specific operational decisions.
7. AI in regulated/healthcare environments. On-prem, HIPAA, data sovereignty work where the AI has to live where the data lives.
8. AI governance and internal AI sandboxes. Building the safe environment where staff can use AI compliantly.
9. Engineering productivity and software factories. AI inside the SDLC, ticket to PR.
10. Custom model and platform builds for AI startups. Helping AI companies build their own products and stand up FDE arms.
11. Evals, benchmarks, and RL environments. Measurement infrastructure that decides whether agents are safe to ship.
12. Data and ML infra for AI workloads. The foundation under everything else: pipelines, GPU clusters, IaC.
13. AI advisory at the strategy and PE portfolio level. Helping investors and operators decide where AI fits.
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@ycombinator @tryscope_app @anandPa94 agents are shipping but most teams are blind to what theyre actually doing. claude code + codex observability is the missing layer
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Scope (@tryscope_app) helps companies see when AI agents choose them, get stuck, or pick a competitor, and what to change to improve it. It runs real workflows across Claude Code, Codex, Cursor, and similar AI agents.
Congrats on the launch, @anandPa94!
ycombinator.com/launches/QK8-s…
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THIS DEVELOPER HASN'T WRITTEN A SINGLE PROMPT TODAY. CLAUDE CODE EXECUTED 318 TASKS WHILE HE WAS BUILDING THE NEXT PROJECT.
he opened claude code in the morning. dropped one massive spec. hit go.
went back to planning.
by end of day - full app. built. tested. iterated. committed.
his coworkers spent the same day copy-pasting prompts into chatgpt. explaining the same task from scratch. every. single. time.
the gap between them isn't skill. it's not experience. it's not even intelligence.
it's one free methodology called Festival.
here's what Festival actually does that vanilla Claude Code doesn't:
claude normally just executes and finishes. it skips features. it doesn't iterate. it has no feedback loops. it doesn't know when something is actually done.
Festival fixes all of that.
you write the spec once. claude turns it into requirement documents. you review. you lock the plan. you launch.
then claude runs in the background - phase by phase. section by section. task by task.
at every level: test → review → iterate → loop back if needed → only then move forward.
318 tasks. running autonomously. while you're already planning the next product.
that's not prompting. that's running a factory.
Khairallah AL-Awady@eng_khairallah1
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@ryancarson yes but the value is actually in helping companies stay fluid and flexible, being reliant on a lab whether OpenAi/Anthropic is a death sentence imo. Fluiditiy is the moat
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I've been saying for a while there's a lot of money to be made in AI service startups. Here we go …
OpenAI@OpenAI
Today we’re launching the OpenAI Deployment Company to help businesses build and deploy AI. It's majority-owned and controlled by OpenAI. It brings together 19 leading investment firms, consultancies, and system integrators to help organizations deploy frontier AI to production for business impact. openai.com/index/openai-l…
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Today we’re launching the OpenAI Deployment Company to help businesses build and deploy AI.
It's majority-owned and controlled by OpenAI. It brings together 19 leading investment firms, consultancies, and system integrators to help organizations deploy frontier AI to production for business impact. openai.com/index/openai-l…
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@jordan_ross_8F it takes like 1 hour to learn obsidian and claude if you have an iq over 70
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Building a second brain for your advertising agency has never been easier.
But most agency owners don't have the time to learn Obsidian + claude code or validate it's even worth their time.
So I put my team to work for you.
196 pages built to help you install, set up, and start using Obsidian to run your agency with claude code powering it behind the scenes.
Inside you'll find:
→ The 5-folder vault structure that scales (plus the CLAUDE.md file that turns Claude into a collaborator who's been reading your notes for months)
→ 29 ready-to-paste plays for daily ops, content, sales calls, client delivery, and strategic thinking
→ The 30-day rollout plan
Comment AY and I'll send it.
Charly Wargnier@DataChaz
Obsidian users right now:
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Just spoke with a couple friends who work on the operational side at very large private equity firms
Every PE firm is now scrambling to find and recruit AI talent who can implement the newest tools into their PortCos
This includes former and current technology executives who are familiar with the industry, as well as engineers who can drop directly into the business to build custom made tools
Will keep the comp numbers confidential but they are absolutely insane, especially at the senior levels
For the PortCos that have already piloted this, the efficiency gains are huge. Some are well within the range of 20%+ headcount reduction potential for back office functions
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