Twitter AI Evaluation

Wednesday, April 1, 2026

AI Evaluated
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@yasser_elsaid_ Save Insight

This is my playbook for bootstrapping an AI agent business to $9M ARR. The most important thing is that you need something repeatable and scalable, something where if you do more of, you get more money. You need the equation where you can arbitrage every dollar you spend into more dollars on the other end. Here is how you get there: 1. if you're in B2B, just do the B2B stuff. self-serve is very hard to make work in B2B. it's so much easier to build a sales team, teach them the product, and let them sell it, instead of building a very intuitive platform and hoping people figure it out. that's why all these bigger companies are mainly doing "book a demo with us." they charge customers a lot more because there's no public pricing, and they can set the product up for them. you cannot rely on a middle manager at a non-tech company to put in the effort to use your platform, even if it's extremely intuitive. if you're bootstrapping, you can't hire a sales team on day one. so you need momentum from self-serve customers first. but the goal is to layer in sales as fast as possible, get on demo calls, set up the product for bigger customers, and invest in building an intuitive platform at the same time. 2. content is non-negotiable, even if you're sales-led. good content gets you brand visibility and brand awareness, and that makes all the other channels work much more efficiently. paid ads work much better if people recognize your brand. if they click on your page and see content that people are engaging with, good quality content, it compounds everything. here's what that looks like: video: it depends on your ICP, but we all know video is hard to do, and that's a good thing because it makes the barrier to entry much higher. you can signal that you are a serious business if you do good quality video content. be creative within video, but don't get too creative with the kinds of videos. the kinds of videos you should be doing are product videos and customer videos. that's it. you can be creative in telling your customers' story, you can be creative in launching a product, but don't do the stunt thing, the office content, the random skits. they can work, but you only do them after you do the things that you know will work. hire a videographer in-house. agencies are so expensive (this is just a good rule of thumb). text + personal brands: you need personal brands for everyone in the company. EGC (employee-generated content) needs to be a non-negotiable. everyone on the team posting at least twice a week. 3. warm outbound is the lowest-hanging fruit. warm outbound = outbounding people who have already seen your product. people who interacted with your LinkedIn posts. people who visited your site but haven't signed up. people who created an account but never finished onboarding. these people are the lowest-hanging fruit. email them, call them, put them in a sequence until they become customers. you can have very clear KPIs for your team on this. 4. cold outbound, if your ICP is big enough. be good at writing cold emails and managing your own infrastructure. don't go through an agency. build a system where you can send emails profitably. if it works, send more. if that works, send more. scale it until it doesn't make sense to continue. also do this in-house if it's an important channel. 5. SEO and AEO are extremely important. whenever I want to try a new product, I ask Claude. AI search is a non-negotiable channel now. you need to show up there. that means a lot of Reddit, a lot of review websites, a lot of talking to blogs and backlinking sites to make sure they write what you want with the messaging you want. 6. expansion: be friends with your biggest customers. get on a call with them. know them by name. they need to have your number. they need to be advocates for you. build community around the customer. a lot of founders do not see their customers as friends or a community. they just see them as revenue. that's so bad. your customers need to enjoy spending time with you and talking with you. 7. pricing is the fastest lever. you need to find a good sweet spot for packaging and pricing. incentivize people to spend more money and make sure it's a good deal for them. there's no shortcut, you talk to customers, see what they care about, see what they get a lot of value out of, and capture some of that value while making sure they're successful. 8. margins don't matter early on. if you have a $10M ARR business but you spend $10M to run it, that's fine. you can always cut costs. revenue is the most important metric. it's easier to cut costs than to make more money, so in the beginning, focus on making more money. That's how we built @chatbase to where it is today. Most of this will continue to scale with us as we go to 100M ARR.

Quick Insight

This is a comprehensive B2B SaaS playbook from someone who actually scaled an AI agent business to $9M ARR. The key insight is prioritizing sales-assisted onboarding over pure self-serve for B2B, plus treating content and warm outbound as force multipliers rather than optional nice-to-haves.

Actionable Takeaway

Start tracking and reaching out to warm leads for his side projects — people who visited landing pages but didn't convert, engaged with posts about his tools, or signed up but never completed onboarding. Build simple email sequences for these audiences before investing in cold outbound.

Related to Your Work

The fintech platform could benefit from the sales-assisted approach rather than pure self-serve, especially for larger merchant partners. For side projects like print-on-demand automation, this validates focusing on direct customer contact over building "intuitive" self-onboarding flows that mid-market customers might abandon.

Thread/Source Worth Reading

Single tweet, no additional links. The value is in the complete framework presented here.

Claude Code leaked their source map, effectively giving you a look into the codebase. I immediately went for the one thing that mattered: spinner verbs There are 187

Quick Insight

Wes Bos found Claude Code's exposed source map and immediately looked at their loading spinner text variations (187 different ones). This is classic developer behavior - when you get a peek behind the curtain of a popular tool, you look for the fun implementation details rather than the serious architecture stuff.

Actionable Takeaway

Nothing concrete here. Brian could check if any of his own apps are accidentally exposing source maps, but that's basic security hygiene he likely already handles.

Related to Your Work

Minor relevance to Brian's Chrome extensions and web agency tools - ensuring proper build configs to avoid leaking source maps in production. Could also inspire better loading states in his fintech dashboards, but 187 spinner messages is overkill for most use cases.

Thread/Source Worth Reading

The link likely goes to the actual spinner verbs list. Mildly entertaining but not particularly valuable - just a collection of loading messages like "Thinking...", "Processing...", etc.

@bcherny Explore Further

I wanted to share a bunch of my favorite hidden and under-utilized features in Claude Code. I'll focus on the ones I use the most. Here goes.

Quick Insight

This is the opening tweet of a thread where @bcherny promises to share specific, lesser-known features in Claude Code (Anthropic's coding assistant). Since Brian heavily uses AI in his dev workflows and builds AI-powered tools, practical tips for getting more out of Claude Code could directly improve his daily productivity.

Actionable Takeaway

Read through the full thread to identify 2-3 Claude Code features Brian isn't currently using, then test them on his next side project or during his fintech work to see if they speed up his TypeScript/AWS CDK development.

Related to Your Work

Brian's building AI-powered dev workflows and could apply these Claude Code features to his fintech platform's webhook integrations or his print-on-demand automation tools. Better AI coding assistance could speed up his TypeScript development and AWS CDK infrastructure work.

Thread/Source Worth Reading

This appears to be the start of a thread with the actual tips coming in follow-up tweets. The thread is likely worth reading since it promises specific, actionable features rather than general AI hype.

@starks_arq Explore Further

Quick Insight

This is a detailed technical playbook for using Seedance 2.0 (AI video generation) for actual production work, not just demos. The key insight is treating it like a real film editor — generating individual shots and stitching them together rather than trying to create full videos in one go.

Actionable Takeaway

Test the VPN + CapCut workflow to access Seedance 2.0, then experiment with the 5-block prompt structure (Subject/Action/Camera/Style/Quality) for generating marketing videos for your side projects or client work.

Related to Your Work

This could streamline content creation for your print-on-demand business and web agency tools — instead of hiring video creators or learning complex editing software, you could generate product demos, explainer videos, and marketing content using the structured prompt approach they've documented.

Thread/Source Worth Reading

Yes, definitely worth reading. The linked article is a comprehensive technical guide with specific prompt structures, workflow decisions, and production techniques. It's practical documentation from people actually using this for commercial work, not theoretical advice.

@NickSpisak_ Explore Further

Quick Insight

This is a detailed setup guide for Claude's "Cowork" feature - an AI agent that can actually interact with your apps and files, not just generate text. For Brian, this could be a game-changer since he's already building AI integrations and automation workflows - having a properly configured AI assistant that connects to his actual tools could streamline both his fintech work and side project management.

Actionable Takeaway

Set up Claude Cowork with the folder structure and global instructions described here. Start with migrating ChatGPT memories, then create the context folder with about-me.md, brand-voice.md, and working-preferences.md files. Test it on a specific workflow like managing side project documentation or automating client communication.

Related to Your Work

This directly applies to Brian's AI-powered dev workflows and could automate parts of his web agency client work. Instead of manually switching between Slack, email, and project management tools for his print-on-demand business or fintech platform, Cowork could handle routine communications and file organization across his multiple projects.

Thread/Source Worth Reading

Yes, worth reading. The linked article provides a complete step-by-step implementation guide with specific folder structures, global instruction templates, and plugin recommendations. It's practitioner-focused rather than theoretical - exactly the kind of tactical content Brian would find useful for immediate implementation.

Another sick upcoming feature: /acp spawn codex --bind here LOOK AT ME, I AM CODEX NOW You could bind codex/claude code/opencode already in threads, now you can take over your current session as well.

Quick Insight

This is showing a new feature in what appears to be an AI coding assistant (likely Claude or similar) where you can spawn a "codex" agent and bind it to your current coding session with a simple command. It's about seamless context switching between different AI models/agents within the same development environment rather than opening separate chat windows.

Actionable Takeaway

Test this /acp spawn codex --bind here command pattern in his current AI coding workflow to see if session binding improves context retention when switching between different coding tasks or AI assistants during development.

Related to Your Work

This could streamline his AI-powered dev workflows for side projects - instead of copy-pasting context between different AI tools when building Chrome extensions or automation scripts, he could maintain session state while leveraging different AI capabilities within the same coding environment.

Thread/Source Worth Reading

No links provided. The tweet is standalone and lacks context about which tool this actually is or how to access it. Would need to check the author's other tweets or replies for implementation details.

Thanks for all your patience as we beefed up remote control. How can we next make this more useful for you? @ files from mobile? Something else?

Quick Insight

Noah (likely from Cursor IDE based on the "@files from mobile" context) is asking for feedback on their remote development features. This suggests they're expanding mobile capabilities for their AI-powered coding assistant, which could be useful for developers who want to code or manage projects on-the-go.

Actionable Takeaway

If Brian uses Cursor, he could reply with specific remote workflow pain points from his side projects - like needing to quickly check deployment logs or update environment variables while away from his main dev machine.

Related to Your Work

For Brian's fintech work and side projects, reliable remote access could help with urgent production issues or quick tweaks to his print-on-demand automation when he's mobile. The "@files from mobile" feature could be particularly useful for reviewing webhook logs or making small config changes.

Thread/Source Worth Reading

This is just a feedback request tweet with no links or substantial thread content. Nothing additional to read.

@Hawks0x Save Insight

Quick Insight

This is a fitness influencer sharing 7 AI prompts for Claude to generate personalized workout plans, injury prevention, and nutrition guidance. It's positioned as replacing expensive personal trainers with AI coaching for free. While the fitness content isn't directly relevant to Brian, the underlying approach of creating detailed, specialized prompts for domain-specific AI coaching could be applied to developer productivity and technical mentoring.

Actionable Takeaway

Create similar prompt templates for technical domains Brian works in - like prompts for code review, architecture decisions, debugging workflows, or startup strategy. The structured approach of having 7 specialized prompts each targeting a specific problem area could work well for developer tooling.

Related to Your Work

This maps directly to Brian's AI-powered dev workflows. Instead of fitness coaching, he could build prompt libraries for fintech compliance reviews, webhook debugging, or serverless optimization. The "argue with your AI coach" concept could be valuable for technical decision-making where you need to iterate and refine solutions.

Thread/Source Worth Reading

The linked article provides 7 detailed fitness prompts but the real value is seeing the prompt structure and iteration approach. Worth skimming to understand how they've formatted domain-specific AI coaching prompts, but the fitness content itself isn't relevant.

@jgreze Explore Further

Quick Insight

This is a product thesis arguing that AI tools should act proactively (like TikTok's algorithm) instead of waiting for user prompts. The author (CEO of Town) claims their platform already achieves 25% prompt-less interactions where AI watches user behavior and takes action automatically. It's a compelling vision but heavy on marketing for their specific product.

Actionable Takeaway

Study how your current AI integrations could shift from reactive (user prompts) to proactive (observing patterns and acting first). For your side projects, experiment with AI that watches user behavior in your Chrome extensions or print-on-demand tools and suggests actions rather than waiting for commands.

Related to Your Work

This directly applies to your fintech platform's analytics dashboards and webhook integrations. Instead of users manually querying data or setting up alerts, AI could proactively surface anomalies, suggest optimizations, or auto-generate reports based on merchant behavior patterns. Your event-driven architecture is already positioned for this kind of proactive AI layer.

Thread/Source Worth Reading

Yes - the linked article is worth reading. It provides concrete examples of proactive AI actions (auto-drafting emails, scheduling meetings, flagging important messages) and includes actual metrics from their platform. The vision is clearer than most AI product thinking pieces, though filter out the company pitch.

@GriffinHilly Explore Further

Quick Insight

This is a comprehensive Claude workflow system that turns AI interactions from random prompts into a structured development process. It's basically a production-ready framework for using Claude as a coding partner with defined roles, project structures, and decision-making patterns.

Actionable Takeaway

Clone the repo and implement the COMP system (CLAUDE.md, ORIENT.md, MEMORY.md, PLAN.md) for one of your side projects. Start with the core CLAUDE.md file to establish the "leverage doctrine" where you think and Claude executes.

Related to Your Work

The webhook integrations and analytics dashboards you build at the fintech startup would benefit from the "Test-First Bug Fixing" and "Operationalize Every Fix" patterns. The delegation templates could streamline how you use AI for research vs implementation in your print-on-demand automation.

Thread/Source Worth Reading

Yes - the GitHub repo contains production-ready templates including 7 agent delegation patterns, project structure templates, and the weekly bookmark processing system. This is a complete framework, not just ideas.

@coreyganim Explore Further

Quick Insight

This is a detailed breakdown of 7 specific Claude plugin business ideas (client onboarding, report generation, content repurposing, etc.) with concrete pricing models ($500-5K setup + $200-500/month). It's essentially a productized AI services playbook targeting agencies and consultants, plus strategies for monetizing existing Anthropic plugins.

Actionable Takeaway

Pick one plugin idea that matches your existing network (likely the weekly report generator or client onboarding for agencies) and build a simple MVP using Claude's API. Test pricing and demand with 2-3 potential customers before investing in full development.

Related to Your Work

The webhook integration and analytics dashboard experience at your fintech startup directly translates to building these plugins. Your AWS CDK/serverless skills would handle the infrastructure, while your side project experience gives you the solopreneur perspective to actually ship and monetize these tools.

Thread/Source Worth Reading

The linked article provides specific pricing models and target customers for each plugin idea, plus three monetization strategies for existing Anthropic plugins. Worth reading for the concrete business details, but the core value is already captured in this breakdown.

@btaylor Explore Further

Today, Sierra is releasing Ghostwriter, our agent for building agents. With Ghostwriter, you can create an AI agent for your customer experience — one that can chat, pick up the phone, speak dozens of languages, take action on your systems of record, and be protected with industry-leading guardrails — simply by having a conversation. No clicking, no forms, no menus. Codex and Claude Code have transformed how we build software, making it possible for software engineers to orchestrate and review the work rather than doing all the work themselves. We think the same transformation will happen for all software. Rather than every enterprise app having a web app for humans and an API for automation, every software platform’s UI will be an agent that can do the work on your behalf. I recorded a demo of my building and optimizing an agent with Ghostwriter so you can see how powerful and easy it is to use. It’s completely changed the way our early adopters build agents, and it’s changed the way I think about the software industry. Let me know what you think, and, if you’re interested in trying it out at your business, please reach out directly.

## Quick Insight

Sierra is announcing Ghostwriter, a conversational tool for building customer service agents that can handle calls, chats, and system integrations. This represents the broader trend of replacing traditional UIs with AI agents, which is highly relevant for Brian's fintech work where customer experience and automation are critical. ## Actionable Takeaway Evaluate Ghostwriter for building customer support agents for his fintech platform's credit-card offers system - could automate merchant onboarding questions, user support for linked accounts, or webhook troubleshooting conversations. ## Related to Your Work Direct application to his fintech startup's customer experience layer. Instead of building traditional support dashboards and forms for merchants integrating offers, he could deploy an agent that handles technical questions about webhook implementations, troubleshoots integration issues, and guides merchants through the onboarding process. ## Thread/Source Worth Reading Tweet mentions a demo video showing the build/optimization process. Worth watching to see the actual workflow and complexity level - could reveal whether this is genuinely no-code or still requires technical sophistication. ## Action EXPLORE_FURTHER ## Tags ai-agents, customer-experience, fintech-tools, automation, no-code

Quick Insight

This is a typical "make money online" pitch using Claude AI to generate Amazon content ideas, then MakeUGC to create promotional videos. The $56k claim is unverified and the approach is essentially automated affiliate marketing/content creation. For Brian, it's mostly noise since he's already building legitimate products, but the automation workflow concept could be interesting.

Actionable Takeaway

Test using Claude AI for content gap analysis on his own products - feed competitor research or user feedback into Claude to identify missing features or content opportunities for his fintech platform or side projects.

Related to Your Work

The validation approach (using AI to analyze market data before building) could apply to his side projects. Instead of Amazon listings, he could analyze Chrome extension reviews, fintech user complaints, or print-on-demand trends to identify automation opportunities before building tools.

Thread/Source Worth Reading

Skip the linked content. It's a standard affiliate marketing course pitch with unverified income claims. The MakeUGC tool might be worth a quick look for his web agency, but the "system" is just basic content automation dressed up as a breakthrough.

@thdxr Explore Further

james has achieved distributed opencode agents can run on your laptop, on a remote server, in a cloud sandbox provider shut your laptop and things keep running open it back up and all the data syncs delete the sandbox nothing is lost

Quick Insight

This describes a distributed development environment where AI agents can seamlessly move between local machines, remote servers, and cloud sandboxes while maintaining state sync. It's essentially "code anywhere, resume anywhere" with AI agents handling the heavy lifting across different compute environments.

Actionable Takeaway

Test this distributed agent setup for his Chrome extension development workflow - start development locally, push heavy processing to cloud sandboxes when needed, and sync back for local testing without losing context or progress.

Related to Your Work

Perfect for his print-on-demand automation and AI-powered dev workflows where he needs to run long-running processes (image generation, API integrations) that shouldn't be tied to his laptop being open. Could handle webhook processing for the fintech platform across distributed environments.

Thread/Source Worth Reading

The linked content likely shows a demo of this distributed agent system in action. Worth checking to see the actual implementation - could be a new tool or framework that enables this behavior rather than just a concept.

@eglyman Explore Further

Since 2023, the top quartile of AI spenders on @tryramp have more than doubled their revenue. Bottom quartile? Flat A roofing company in Texas. A window installer in Utah. A construction firm in Florida that grew 65% The gap is accelerating and most companies don't feel it yet

Quick Insight

This is showing real business data from Ramp's expense platform: companies spending heavily on AI tools are significantly outperforming those that aren't, with the gap widening. It's not just tech companies - traditional businesses like construction and roofing are seeing major revenue growth from AI adoption.

Actionable Takeaway

Audit his fintech startup's current AI spend and identify where they could be investing more aggressively in AI tooling - whether for customer support, data analysis, or development workflows. The data suggests being conservative on AI investment might be leaving growth on the table.

Related to Your Work

For his fintech platform handling credit-card-linked offers, this validates investing in AI for merchant analytics, fraud detection, or personalized offer matching rather than treating AI tools as "nice-to-haves." The expense data shows AI investment correlating directly with revenue growth.

Thread/Source Worth Reading

The tweet has links that likely contain more detailed breakdowns of the spending patterns and case studies from the construction companies mentioned. Worth checking for specific AI tools and use cases driving the revenue growth.

Wowza - ya'll have created a ton of these already . What are you using these for?? Would love to set up some calls!

Quick Insight

Noah is asking about user adoption and use cases for something people have "created a ton of" - but without the linked content or context, this is essentially meaningless. It's a generic engagement post fishing for user feedback on an unclear product/tool.

Actionable Takeaway

Nothing actionable here - the tweet lacks specifics about what tool or product is being discussed, making it impossible to evaluate or act on.

Related to Your Work

Can't determine relevance without knowing what "these" refers to. Could be anything from AI agents to Chrome extensions to fintech tools.

Thread/Source Worth Reading

The linked content (https://t.co/oa6GICwIYn) would need to be checked to understand what this tweet is actually about. The tweet itself provides zero context.

@aidenybai Explore Further

Introducing Expect Let agents test your code in a real browser 1. Run Claude Code / Codex to QA your app 2. Watch a video of every bug found 3. Fix and repeat until passing Run as a CLI or agent skill. Fully open source

Quick Insight

This is announcing "Expect" - a tool that lets AI agents (Claude, etc.) automatically test web apps by actually running them in browsers, recording videos of bugs they find. It's automated QA testing powered by AI agents that can see and interact with your UI like a human would.

Actionable Takeaway

Try running Expect on one of his Chrome extensions or print-on-demand tools to see how AI agents perform compared to his current manual testing workflow. The CLI approach would fit well into his existing dev processes.

Related to Your Work

Perfect for his fintech platform's webhook integrations and analytics dashboards - areas where UI bugs can break critical user flows. Could also automate QA for his web agency tools, freeing up time to focus on building features instead of manual testing.

Thread/Source Worth Reading

Yes - the linked repo will show implementation details, setup instructions, and examples of what the AI agents can actually catch. Worth checking if it integrates with his existing TypeScript/serverless stack.

@mattwelter Explore Further

i wasted my entire life because nobody told me i could do this

Quick Insight

This is a classic "life-changing discovery" hook tweet with a link, likely promoting some tool, course, or workflow that Matt claims would have saved him years of effort. Without seeing the linked content, it's pure clickbait - could be anything from a productivity system to a coding technique to a business strategy.

Actionable Takeaway

Click through to see what specific tool/approach Matt is promoting, then evaluate if it's actually relevant to your current stack or workflows. Most of these "wish I knew this earlier" posts are overselling basic concepts.

Related to Your Work

If it's a legitimate development tool, automation workflow, or AI integration technique, it could apply to your fintech platform's webhook processing or your side project automation pipelines. But that's a big "if" without knowing the actual content.

Thread/Source Worth Reading

The linked content is the entire point of this tweet. Need to check if it's actually valuable or just typical Twitter hyperbole around a basic concept dressed up as revolutionary insight.

@MitcheIl Explore Further

Quick Insight

This is a detailed breakdown of a 20-agent AI system for writing video scripts that allegedly generated $10M+ revenue for clients. The system uses specialized agents for research, writing, and quality control, with each agent having specific scoring criteria and iterative improvement loops. While the revenue claims are hard to verify, the multi-agent workflow design with quality gates is a solid architectural pattern.

Actionable Takeaway

Build a simplified version for your side projects — create 3-4 specialized Claude agents (research, writing, editing, scoring) with specific prompts and quality criteria for generating marketing copy for your print-on-demand or web agency tools. Start with one content type and expand.

Related to Your Work

This multi-agent approach could work for your fintech platform's content generation — specialized agents for compliance review, feature explanations, and customer communication. The "weapons check" scoring system could be adapted for validating webhook documentation or generating analytics dashboard explanations.

Thread/Source Worth Reading

Yes, worth reading. The breakdown shows specific implementation details like the research methodology (ceiling/floor view patterns, 5K posts via X API) and the agent specialization structure. The quality scoring system (Invention Novelty + Copy Intensity) is a practical framework you could adapt for other AI workflows.

@mvanhorn Explore Further

Quick Insight

This is a detailed workflow breakdown of using Claude Code with heavy automation - planning everything in structured markdown files before coding, dictating via voice, and running multiple AI sessions simultaneously. The author has essentially replaced traditional IDE work with AI-driven planning and execution, claiming 80% planning vs 20% coding instead of the reverse.

Actionable Takeaway

Try the Compound Engineering plugin for Claude Code and adopt the /ce:plan before /ce:work discipline on your next side project feature. Start with one workflow - maybe Chrome extension bug fixes - where you force yourself to create a plan.md before touching code.

Related to Your Work

This directly applies to your webhook integration work and AI-powered dev workflows. The parallel session approach could streamline your fintech platform development - one session planning credit card offer features, another building analytics dashboard components, another debugging webhook failures.

Thread/Source Worth Reading

Yes - this is a comprehensive deep-dive into a complete AI-first development workflow. The config settings, plugin setup, and voice integration details are immediately actionable. The author has real metrics (70 plans, 263 commits) backing up the approach, not just theory.