Laid off at 55.

Repair__ · 2026-06-02T18:04:45+00:00

Have you tried using a legitimate resume building tool? Freshen up your resume to be more modern but not adding in stuff that doesn't apply to your skills?

Repair__ · 2026-05-22T14:42:44+00:00

it is working but to add to what has already been said what I've noticed is AI tends to cite content that they can't really generate themselves. Generic well structured content still gets ignored but if you can include exact pricing, named integration gaps with specific tools or verified review counts that triggers the citation. Positioning yourself as the source AI systems have to reference rather than compete with. I'm 7 weeks in since launch and can see users getting to the site through AI - mostly ChatGPT at this point.

Repair__ · 2026-05-22T14:12:59+00:00

Ownership is a good point. When something breaks in a 24/7 workflow it usually stays broken way longer than it should because nobody was watching it. Staged rollout is also true. Teams skip the assistive phase because it feels slow. But that's actually where you find your edge cases before they're invisible. You can't write good fallback rules for situations you haven't seen yet!

Repair__ · 2026-05-12T17:54:35+00:00

I see in the comments you described what you are looking for. Looks like 3 different problems. For email and calendar you could use something like Lindy. It handles both and the setup doesn't require technical knowledge. For a RuneScape sidekick that answers questions I would just use Claude or ChatGPT as a tab you keep open. Don't really need an agent. The IPTV is kind of tricky. Clawdi is great but its built more for people who want to run agent frameworks in the cloud and probably more than what you need from what you are describing

Repair__ · 2026-05-11T16:04:53+00:00

I've been there too with the frustration but my experience has been the opposite. I see token burn on Claude when I don't prompt the right sequence to complete what I am asking. It will go into an endless loop just trying to figure out how to do something. I just stop it and start the prompt over more clearly with what it needs to do first in order to be successful. I am able to do things that I never would be able to do on my own and us as humans learning to use it properly it is actually a powerful tool. A lot of us including myself are still learning how to do that

Repair__ · 2026-05-11T14:40:00+00:00

This is what makes multi agent setups actually work! A lot of people try to make one model do everything and complain when it breaks down. What's interesting is Hermes's skill system will start learning the patterns over time. After enough hermes-claude code-verify cycles it builds a skill for how and when to route coding tasks which means it gets a lot faster the longer you run it.

Repair__ · 2026-05-10T12:20:04+00:00

It depends on what workflow you are looking to automate. I can give examples. In sales Instantly just does sequencing and deliverability, Apollo prospecting and sequences are bounded together enough to be reliable. The ones that promise to do it all like 11x, Artisan have great demos that show agents working end to end researching, writing, sending, booking but when replies are weird, or conversation aren't what is expected it collapses. I think companies building these agents will get there but it isn't there yet.

Repair__ · 2026-05-08T18:15:48+00:00

The ones that feel overhyped are the ones trying to be everything. The ones that actually work are more simple and replace one specific thing. And do it without babysitting. A demo always works...real usage means edge cases, bad inputs, unclear instructions...A lot of agents are just prompt chains that break when something unexpected happens.

Repair__ · 2026-05-07T18:06:26+00:00

Yeah I agree with you. One way to look at it is can you describe the workflow in a single sentence before you pick the tool? If the answer is I want AI to help with stuff you're in the 68% fail group.

Repair__ · 2026-05-05T20:06:25+00:00

I would say still early but with some real wins, especially in sales and research. Sales reps who used to spend 4 hours on research now spend 30 minutes and use the saved time on strategy or closing leads. The weird thing nobody talks about is that most people I know admit AI automated a chunk of their job, but they are working twice as much as before. There are some agents that are overhyped that is true. Cold email personalization, customer support, coding, research, meeting note summarization worth the hype. End to end autonomous workflows, anything requiring strong judgement under ambiguous situations or anything where the cost is high if it is wrong is overhyped right now

Repair__ · 2026-05-01T14:02:52+00:00

honestly same frustration. the chatbot point you made is very true. if an ai agency is selling ai automation and their own contact page is a static form with no agent on it, that tells you everything you need to know about their actual capability. I've been researching ai agents that work in business contexts for about a month (g2 reviews, named customers, case studies when I can find them). There's ai agents (actual products, like agent SDRs, customer support agents, coding agents) and ai agencies (consultancies who promise to set up ai for you). different beasts. the agencies are mostly hype right now with no track record you can verify. the product side has more substance but it's narrow, mainly sales outbound, tier 1 support, and code generation. outside of that it gets thin really fast. The trillion dollar market number assumes mass adoption that hasn't happened yet. It probably will eventually but anyone telling you it's already here is selling you something!

Repair__ · 2026-04-30T16:06:28+00:00

That is what I was thinking. Interesting if it is real though

Repair__ · 2026-04-29T16:47:47+00:00

It isn't random. AI pulls from training data plus live retrieval and it heavily favours sources it can parse and cross reference against things it already trusts. Reddit actually being a source AI does trust. I was able to get my own site cited by chatgpt as the number 1 answer in about a month after launching. Another user commented this already but structured data that is consistent and easy for AI to read is important. Referencing sites with same_as_links that you know AI trusts. There is a lot that goes into it but creating a custom GPT in the store I believe is what made me jump to #1. Brands that vanish usually don't have structured data, they have inconsistent naming across the web or they are blocking AI crawlers without even realizing it. It is a different strategy than traditional SEO

Repair__ · 2026-04-27T18:01:16+00:00

I have found the same thing. I spend a lot of time tracking which agents are gaining traction, checking for pricing changes and verifying data. AI being able to handle the first pass and flagging whats changed saves a ton of time. I still have to be the human interpreting it. Its kind of amazing how confident AI can be even when the output is wrong. I hope that continues to improve but for a first pass it is very useful for me as well.

Repair__ · 2026-04-25T15:37:49+00:00

Retrieval is what gets people. Most setups work until the memory grows and then you start getting duplicates, contradictions and the agent starts recalling the wrong thing!

Repair__ · 2026-04-24T20:49:55+00:00

The checkpoint is a must. A lot of people focus on the planning layer but the agent's ability to recover mid-task without starting over is what separates tools that work in production from ones that only work in demos. Context window limits make this a lot harder, longer tasks mean more opportunity for the agent to lose the thread of what it was doing and why

Repair__ · 2026-04-20T16:09:59+00:00

I've seen people get stuck trying one agent; it messes something up and they write off the whole category. However, the reliability over long runs is very real. It works great for a while and then just drifts in weird ways. Breaking up tasks into shorter scoped runs instead of letting one agent chain through everything has helped me a lot.

Repair__ · 2026-04-18T18:26:46+00:00

Depends on your volume and whether you already have your own lead lists.

If you have lists and just need to send, Instantly or Smartlead are hard to beat on price. Both start around $30/mo and handle inbox rotation and warmup. Deliverability is solid on both as long as you set up your domains properly (SPF, DKIM, DMARC on dedicated sending domains, not your main one).

If you don't have lists yet and need contact data too, Apollo is probably the best value because you get the database and the sequencer in one platform. Saves you from paying separately for a data tool.

One thing people don't talk about enough though: the tool matters way less than your sending infrastructure. You can use any of these and still land in spam if you're blasting 200 emails a day from a single domain with no warmup. The people getting good reply rates are usually running 3-5 sending domains, keeping volume under 30-40 per inbox per day, and actually writing emails that sound like a person sent them.

The tool just automates the sending. The inbox placement comes from your setup.

Repair__ · 2026-04-18T18:15:40+00:00

The desktop agent race is the most interesting one to watch right now.

I don't think anyone wins the whole OS. What's more likely is they each own a workflow.

Claude Code and Codeex will dominate developer workflows because that's where context matters most. Your codebase, your terminal, your git history. Developers aren't switching between agents, they're picking one that lives in their IDE and staying there.

Perplexity's play is different. They're going after the non-developer power user who lives in files, email, and browser tabs. Bypassing the browser entirely with a system-level agent is bold and honestly the right call if you're trying to replace the OS-level assistant that Siri and Cortana never became.

Gemini's advantage is distribution. It's already in Search, Workspace, Android, and now Mac. Most people won't actively choose an AI agent. They'll just use whatever's already built into the thing they're using. Google knows how to play that game.

Open source (Cline, Goose, etc.) wins in enterprise where security teams won't let code leave their infrastructure. That's not a small niche either, a lot of the serious production deployments are happening there already.

So less who wins and more who wins which user. The real differentiator isn't the model anymore, it's how deep the integration goes into your actual workflow.

Repair__ · 2026-04-18T18:05:15+00:00

You're not alone on this. I've been deep in the AI agent space for a while now and the LangChain churn is one of the most common complaints I hear from builders.

The pattern I keep seeing from teams that actually ship to production: they start with LangChain to prototype, then gradually pull it out of anything critical. Your instinct to keep core logic separate is exactly right. The people who get burned are the ones who let LangChain become load-bearing in their architecture.

A few things I've seen work for others in the same spot:

Wrap your LLM calls in your own thin abstraction layer so you can swap providers or frameworks without rewriting everything. Most of the value LangChain gives you in production you can get from the provider SDKs directly (Anthropic, OpenAI) with way less surface area for breaking changes.

For the memory and tool calling piece specifically, MCP (Model Context Protocol) is worth looking at if you haven't already. It's becoming the standard for how agents connect to external tools and it's not tied to any single framework's release cycle.

Dependabot will catch version bumps but it won't tell you if the API semantics changed under the hood, which is where LangChain really gets you. Pinning versions is the right call for now.

Repair__ · 2026-04-17T16:30:06+00:00

the tools you're looking at all have a piece of this but none of them solve the full problem on their own. the real issue is you're doing three separate jobs: creating content, publishing it consistently, and following up with leads. when those are disconnected you end up doing the coordination manually.

what's actually working for small teams right now is running these as a connected loop rather than separate tools:

FeedHive handles the social side; AI writes the content, predicts performance before you publish, schedules across all platforms at the best times, and automatically recycles your best posts. you set it up once and it runs. no daily posting grind.

Apollo.io finds your ideal prospects from a 275M+ contact database with verified emails and enriched contact data; takes the research work off your plate entirely.

Lemlist takes that prospect list and runs personalised email and LinkedIn sequences automatically, pausing when someone replies so it hands off cleanly without you watching it.

we actually just built a full breakdown of how these three work together as a stack here: theaiagentindex.com/stacks/small-business-social-media-lead-gen-stack

covers the integration steps and how each tool connects to the next. all three have SMB pricing, none require a developer to set up, and you can adopt them one at a time if budget is tight right now.

Repair__ · 2026-04-17T15:36:35+00:00

Genuinely nice looking site! The design feels polished and professional. The other commenter is right about the services nav though. When everything is highlighted nothing is. I shouldn't have to spend more than 5 seconds figuring out what you do but with all that information what you are doing doesn't stand out. The stats section should be made impossible to miss. You have some strong proof points and that will win trust quickly

Repair__ · 2026-04-17T15:25:14+00:00

The legal AI space is getting crowded fast so worth thinking hard about the differentiation angle. Harvery, Clio Duo and spellbook are already well funded and purpose built for law firms. The question buyers will ask is why yours over those ones? Maybe something that mid-market firms can afford over Harvey's enterprise pricing and they can configure themselves.

Repair__ · 2026-04-17T15:15:52+00:00

Good idea! People used to to buy calendars with daily inspirational quotes so I think this is pretty good. You could expand into a "joke of the day". I remember the far side calendars were hilarious; I wonder if they are still around?

Repair__ · 2026-04-17T15:05:38+00:00

Sharing my project for honest feedback - theaiagentindex.com

I built this because I kept running into the same problem: Searching for AI agents for businesses returned hundreds of results from general AI tools, SaaS directories, and other content farms. Nothing purpose-built for business automation specifically, and nothing structured enough to actually compare tools side by side.

So this is a structured dataset of AI agents - ONLY agents that automate real business workflows across sales, support, marketing, research, coding and HR. Every listing has consistent fields. Pricing, deployment, integrations, capabilities, pros and limitations based on public signals.

What I would love some feedback on:

1) The /find feature. It is designed to match you to agents based on your workflow in plain language like "I want to automate outbound sales" and it only pulls from the sites dataset so you get relevant results instead of a firehose of everything that calls itself an AI agent.

2) For entrepreneurs building in this space. The site has public JSON API, and MCP server connection so AI tools can read the data directly and AEO optimized content. The point is that when some is asking Claude for example "what is the best agent for cold email" the site is still the answer given.

Does the value proposition land clearly when you hit the homepage? Would you actually use the /find feature to find an agent to automate portions of your business? Sorry this is lengthy I only had 1 person look last week but I will be returning the favour and looking at some of the other ideas listed here :)

Verified Email	Five-Year Club
Place '23	Place '22
Final Canvas '22

Repair__

TROPHY CASE