SGP, the Guru

2K posts

SGP, the Guru

SGP, the Guru

@guruprasad

I am the I AM

Eden Prairie, MN Katılım Mart 2007
566 Takip Edilen100 Takipçiler
SGP, the Guru
SGP, the Guru@guruprasad·
@GergelyOrosz Remember YouTube made movie making obsolete and all directors to pivot to cattle rearing.
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Gergely Orosz
Gergely Orosz@GergelyOrosz·
You should probably stop listening to anyone and everyone who said these SaaS companies will “die” soon. And also do some critical thinking + understanding of how business works (and why) if you ever believed it would be true
Jason ✨👾SaaStr.Ai✨ Lemkin@jasonlk

We're back. The B2B Reacceleration Is Real. Twilio, Atlassian, Datadog, Cloudflare, and Palantir just proved it. HubSpot and Shopify still have to. Seven of B2B's most-watched names released earnings this week. Growth is back: 🟣 Datadog: First $1B quarter ever. 32% growth. Stock +28%, biggest pop ever. 5 products at $100M+ ARR. Anthropic on an 8-figure deal. 🔴 Twilio: 4% → 20%. Highest growth in 3 years. Voice fastest in 19 quarters. 🔵 Atlassian: 32% growth, stock +30% in a day. Cloud reaccelerated to 29%. Rovo customers grow ARR at 2x non-Rovo. 🔵 Cloudflare: 34% growth + 1,100-person workforce cut on the same day to "go AI-first." Revenue accelerating, headcount restructuring on the back of internal AI productivity. First time I've seen this combo at this scale. 🟡 Palantir: 85% growth. Highest ever as a public company. US revenue +104%. Rule of 40 = 145%. 11 straight quarters of acceleration. 🟠 HubSpot: Beat the quarter but the "reacceleration" disappears in constant currency. Held the line at 18% CC for 5 straight quarters. Bears were wrong, seats + customers strong. But AI reacceleration hasn't started yet. 🟢 Shopify: $100B GMV quarter. Strong, but pinned in the same 27-34% band for 7 quarters. Q2 guided down to high-twenties. AI commerce is still a slide, not a dollar. 3 things this tells founders: - The "AI is killing B2B" narrative peaked at the bottom. Even the names that didn't reaccelerate held. - Reacceleration shows up as a step-function, not a trend. - AI products tied to measurable revenue lift get rerated. AI features and positioning get a multiple haircut. Atlassian (Rovo +2x ARR), Twilio (voice acceleration), Datadog (Anthropic deal), Cloudflare (workforce restructure on internal AI), Palantir (entire company) all got rewarded. HubSpot and Shopify got sold or held flat. The bottom seems in. For those that have found how to tap into AI budget. Per-seat pricing isn't dead. Vibe coding didn't kill these leaders. But the agents are still coming.

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Gergely Orosz
Gergely Orosz@GergelyOrosz·
Remember these predictions? “Software engineering will be dead because of AI” —> we’re seeing more demand for sw engineering (good part thanks to AI) “SaaS will be dead because of AI” —> SaaS businesses growing massively (in part thanks to AI) Be careful what you believe
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Mahalingam Ponnusamy
Mahalingam Ponnusamy@mahajournalist·
In the Tamil Nadu Assembly, it set to be Vijay Vs Udhayanidhi. எதிர்கட்சி தலைவராகிறார் உதயநிதி
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SGP, the Guru
SGP, the Guru@guruprasad·
@levie Add the fact enterprise IT needs labor to capitalize in books. Buy agentic licenses, non-capital tech expense. Enterprise IT on internal chargeback eals with paradox of increasing license cost, reducing manual labor (revenue). Who's tackling this? Not making this sh1t up
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Aaron Levie
Aaron Levie@levie·
Agentic coding is a huge boon for software developers that want to get far more done, great for IT people to build vastly more custom systems internally, great for domain experts that want to automate workflows or wire systems together, and absolutely fantastic for anyone curious to learn how to start coding. What it’s less great for is casually building complex software that you have to maintain on an ongoing basis and take on all the risk for. Upgrades, maintenance, keeping up to date with latest security issues, and so on, are taxes most knowledge workers aren’t familiar with or prepared for. Net net: we’re going to get 100X more software and vastly more software developers in the future. But that’s different from *everyone* rolling their own.
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SGP, the Guru
SGP, the Guru@guruprasad·
@Grady_Booch Well.. Code creation, documentation, maintenance through automated faster interpreter systems on higher compute using plain business english.. isn't that awesome? Anyone can code, as long as adherence to engg discipline. Why people dissing cobol which is Common business...?
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Grady Booch
Grady Booch@Grady_Booch·
It is a source of continuous delight to watch the AI community rediscover the fundamentals and the dynamics of software engineering as they take those things and embellish them with AI adjectives, making them sound all fresh and new and sparkly while in truth, those fundamentals remain, well, fundamental. Remove AI from the discourse below, and what Andrew promotes are things one heard all the time as we saw - starting decades ago - the transition from assembly language to FORTRAN and COBOL, from structured to object-oriented, from waterfall to agile. The past, as is said, does not repeat itself but rather rhymes. Don’t get me wrong: I celebrate what Andrew et al are doing: developing software-intense systems that are meaningful and that endure requires intention and discipline, and I embrace that. Two dangling threads before I close: I don’t grok the semantics of “traditional teams”. The cosmos of computing is so wide and deep and diverse and crosses so many domains, I conclude that “traditional teams” is what one says when their experience is in a relatively narrow space, and they are witnessing a shift from what they grew up with in the Valley in particular, where web-centric systems of global elastic scale remain the primary focus. Second, I am dismayed at the focus on speed. If you are driving head long Thelma and Louise style toward an IPO then certainly speed will be a critical factor. But for most of the domain of computing, for systems that are meaningful and that endure, other factors are far more important: correctness, repeatability, safety, maintainability, these dominate, and as such, don’t be distracted by the noise and smoke and heat and light of an AI first style that may get you out of the starting gate quickly, but will fail you in the ultra marathon of most development.
Andrew Ng@AndrewYNg

AI-native software engineering teams operate very differently than traditional teams. The obvious difference is that AI-native teams use coding agents to build products much faster, but this leads to many other changes in how we operate. For example, some great engineers now play broader roles than just writing code. They are partly product managers, designers, sometimes marketers. Further, small teams who work in the same office, where they can communicate face-to-face, can move incredibly quickly. Because we can now build fast, a greater fraction of time must be spent deciding what to build. To deal with this project-management bottleneck, some teams are pushing engineer:product manager (PM) some teams are pushing engineer:product manager (PM) ratios downward from, say, 8:1 to as low as 1:1. But we can do even better: If we have one PM who decides what to build and one engineer who builds it, the communication between them becomes a bottleneck. This is why the fastest-moving teams I see tend to have engineers who know how to do some product work (and, optionally, some PMs who know how to do some engineering work). When an engineer understands users and can make decisions on what to build and build it directly, they can execute incredibly quickly. I’ve seen engineers successfully expand their roles to including making product decisions, and PMs expand their roles to building software. The tech industry has more engineers than PMs, but both are promising paths. If you are an engineer, you’ll find it useful to learn some product management skills, and if you’re a PM, please learn to build! Looking beyond the product-management bottleneck, I also see bottlenecks in design, marketing, legal compliance, and much more. When we speed up coding 10x or 100x, everything else becomes slow in comparison. For example, some of my teams have built great features so quickly that the marketing organization was left scrambling to figure out how to communicate them to users — a marketing bottleneck. Or when a team can build software in a day that the legal department needs a week to review, that’s a legal compliance bottleneck. In this way, agentic coding isn’t just changing the workflow of software engineering, it’s also changing all the teams around it. When smaller, AI-enabled teams can get more done, generalists excel. Traditional companies need to pull together people from many specialties — engineering, product management, design, marketing, legal, etc. — to execute projects and create value. This has resulted in large teams of specialists who work together. But if a team of 2 persons is to get work done that require 5 different specialities, then some of those individuals must play roles outside a single speciality. In some small teams, individuals do have deep specializations. For example, one might be a great engineer and another a great PM. But they also understand the other key functions needed to move a project forward, and can jump into thinking through other kinds of problems as needed. Of course, proficiency with AI tools is a big help, since it helps us to think through problems that involve different roles. Even in a two-person team, to move fast, communication bottlenecks also must be minimized. This is why I value teams that work in the same location. Remote teams can perform well too, but the highest speed is achieved by having everyone in the room, able to communicate instantaneously to solve problems. This post focuses on AI-native teams with around 2-10 persons, but not everything can be done by a small team. I'll address the coordination of larger teams in the future. I realize these shifts to job roles are tough to navigate for many people. At the same time, I am encouraged that individuals and small teams who are willing to learn the relevant skills are now able to get far more done than was possible before. This is the golden age of learning and building! [Original text: deeplearning.ai/the-batch/issu… ]

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Rhys
Rhys@RhysSullivan·
@bentossell It can add groceries to my Amazon fresh cart, it updated my insurance info copying it from the anthem website to one medical and scheduled an appointment, it found and booked an Airbnb for me And it all just worked unlike every other approach I’ve tried
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Ben Tossell
Ben Tossell@bentossell·
what's computer use enable that the agent couldn't run a command for previously? genuinely asking
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SGP, the Guru
SGP, the Guru@guruprasad·
@jyothiwrites In fact, it may not even impact human life of earth, yet an AGI evolution will happen in difft dimension. In our world AI yielding productivity , and physical world limitation might help us progress humanoid. Probably just stop at that. (N/n)
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SGP, the Guru
SGP, the Guru@guruprasad·
@jyothiwrites Multiple points to consider in my opinion. 1. If LLMs are restricted to non-biological world, and removed the physically existent need, and interactions are limited to "no muscle memory" need, would that constitute the reality in that world and be the AGI there? (1/n)
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SGP, the Guru
SGP, the Guru@guruprasad·
@jyothiwrites In my brain, it's the triumvirate of quantum modeling for multithreaded possibilities continuation + smart contracts for immutability and traceability + GenAI model as frontier model, fused into a digital altiverse is akin to AGI within that dimension of verse (6/n)
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SGP, the Guru
SGP, the Guru@guruprasad·
@jyothiwrites ... Using let's say quantum cloud... the context and relearning becomes continuous. And multi threading becomes real. (5/n)
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SGP, the Guru
SGP, the Guru@guruprasad·
@jyothiwrites LLMs get the same. Only limitation is physical world interface. If that constraint is removed, and the "world" or the "verse" is limited to digital (I didn't have better name), isn't that the evolution? Computationally the hallucinations and context can be expanded (4/n)
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SGP, the Guru
SGP, the Guru@guruprasad·
@jyothiwrites Being stochastic parrot is not limiting yet emerging knowledge base... Humans acquired aggregated knowledge through muscle memory and recorded memory. This recorded memory in today's world is all through media. Gen Z is fed through Internet. This is coded, recorded. (3/n)
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SGP, the Guru
SGP, the Guru@guruprasad·
@jyothiwrites Well what I mean... Consider MetaVerse as the next universe for evolution, and remove biological and emotional constraints. Then it becomes new world. Life thrives in that digital world and let's say word "life cycle" is kill switch of process, wouldn't it be AGI there? (2/n)
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Ashley Manek
Ashley Manek@AshManek·
@grok For best results in which specific situations do you recommend using this particular model council approach (brainstorming and others?) and when to avoid? Some testers say leave Perplexity Computer to decide what's best on each task so this post seems to contradict that idea
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Computer
Computer@AskPerplexity·
You can now run three frontier models at once and select your orchestrator model directly inside Perplexity Computer. Model Council automatically runs GPT-5.4, Claude Opus 4.6 and Gemini 3.1 Pro simultaneously. Three frontier models. One workflow. Best answer wins.
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SGP, the Guru
SGP, the Guru@guruprasad·
@SriramMadras You recognize Girnus is a satirical writer right? And not a diplomat...
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Sriram
Sriram@SriramMadras·
TWEET OF THE CENTURY👇
Peter Girnus 🦅@gothburz

I am a diplomatic aide in the Sultanate of Oman's Ministry of Foreign Affairs. My job is logistics. When two countries that cannot speak to each other need to speak to each other, I book the rooms. I prepare the briefing materials. I make sure the water glasses are the right distance apart. You would be surprised how much of diplomacy is water glasses. Too close and it feels informal. Too far and it feels like a tribunal. I have a chart. We had a very good month. Since January, Oman has been mediating indirect talks between the United States and Iran on Iran's nuclear program. The talks were held in Muscat and in Geneva. The Americans would sit in one room. The Iranians would sit in another room. I would walk between them. My Fitbit says I averaged fourteen thousand steps on negotiation days. The hallway between the two rooms at the Royal Opera House conference center is forty-seven meters. I walked it two hundred and twelve times in February. This is good for my cardiovascular health. It was less good for my knees. Both are in the service of peace. By mid-February, we had something. Iran agreed to zero stockpiling of enriched uranium. Not reduced stockpiling. Zero. They agreed to down-blend existing stockpiles to the lowest possible level. They agreed to convert them into irreversible fuel. They agreed to full IAEA verification with potential US inspector access. They agreed, in the Foreign Minister's phrase, to "never, ever" possess nuclear material for a bomb. I have worked in diplomacy for seven years. I have never seen a country agree to this many things this quickly. I made a spreadsheet of the concessions. It had fourteen rows. I color-coded it. Green for confirmed. Yellow for pending. By February 21 the spreadsheet was entirely green. I printed it. It is on my desk in Muscat. It is still green. That phrase took eleven days. "Never, ever." The Iranians initially offered "not seek to." The Americans wanted "will not under any circumstances." We landed on "never, ever" at 2:14 AM on a Tuesday in Muscat. I typed the final version myself. I used Times New Roman because Geneva prefers it. The document was fourteen pages. I was proud of every comma. Here is what they said, in the order they said it. February 24: "We have a once-in-a-generation opportunity." — The Foreign Minister, private briefing to Gulf Cooperation Council ambassadors. I prepared the slide deck. Slide 14 was the implementation timeline. Slide 15 was the signing ceremony logistics. I had reserved the Palais des Nations in Geneva, Room XX. It seats four hundred. We discussed pen brands for the signing. The Iranians preferred Montblanc. The Americans had no preference. I ordered twelve Montblanc Meisterstucks at six hundred and thirty dollars each. They arrive on Tuesday. February 27, 8:30 AM EST: "The deal is within our reach." — The Foreign Minister, CBS Face the Nation. He sat across from Margaret Brennan. He said broad political terms could be agreed "tomorrow" with ninety days for technical implementation in Vienna. He said, and I wrote this line for the briefing card he carried in his breast pocket: "If we just allow diplomacy the space it needs." He praised the American envoys by name. Steve Witkoff. Jared Kushner. He said both had been constructive. I watched from the Four Seasons Georgetown. The minibar had cashews. I ate the cashews. They were nineteen dollars. The most expensive cashew I have ever eaten. But it was a good morning and we were within our reach. February 27, 2:00 PM EST: Meeting with Vice President Vance, Washington. The Foreign Minister presented our progress. Zero stockpiling. Full verification. Irreversible conversion. "Never, ever." The Vice President used the word "encouraging." His aide took notes on an iPad. The aide did not make eye contact for the last nine minutes of the meeting. I noticed this. Noticing things is the only part of my job that is not water glasses. February 27, 4:00 PM EST: "Not happy with the pace." — President Trump, to reporters. Not happy with the pace. We had achieved zero stockpiling. Full IAEA verification. Irreversible fuel conversion. Inspector access. And the phrase "never, ever," which took eleven days and cost me two hundred and twelve trips down a forty-seven-meter hallway. Every American president since Carter has failed to get Iran to agree to this. Forty-five years. Not happy with the pace. February 27, 9:47 PM EST: The Foreign Minister's flight departs Dulles for Muscat. I am in the seat behind him. He is reviewing Slide 14 on his laptop. The implementation timeline. Vienna technical sessions. The signing ceremony. The pens. I fall asleep over the Atlantic. I dream about water glasses. February 28, 6:00 AM GST: I wake up to push notifications. February 28: "The United States has begun major combat operations in Iran." — President Trump. Operation Epic Fury. Coordinated airstrikes. The United States and Israel. Tehran. Isfahan. Qom. Karaj. Kermanshah. Nuclear facilities. IRGC bases. Sites near the Supreme Leader's office. Israel called their half Operation Roaring Lion. Someone in both governments spent time choosing these names. Epic Fury. Roaring Lion. I spent eleven days on "never, ever." They spent it on branding. The President said Iran had "rejected American calls to halt its nuclear weapons production." Rejected. Iran had agreed to zero stockpiling. Iran had agreed to full verification. Iran had agreed to "never, ever." Iran had agreed to everything in a fourteen-page document that I typed in Times New Roman. The President said they rejected it. I do not know which document the President was reading. I know which one I typed. February 28, 18:45 UTC: Iran internet connectivity: four percent. — NetBlocks, confirmed by Cloudflare. Ninety-six percent of a country went dark. You cannot negotiate with a country at four percent connectivity. You cannot negotiate with a country that is being struck. You cannot negotiate. This is not a political opinion. This is a logistics assessment. February 28: The governor of Minab reported forty girls killed at an elementary school. I do not have logistics for that. There is no slide for that. The water glass chart does not cover that. February 28: Lockheed Martin: up. Northrop Grumman: up. RTX: up. Dow futures: down six hundred and twenty-two points. Gold: five thousand two hundred and ninety-six dollars. An analyst at AInvest published a note titled "Iran Strikes: Tactical Plays." The note recommended positions in oil, defense stocks, and gold. The most expensive cashew I have ever eaten was nineteen dollars. The most expensive pen I have ever ordered was six hundred and thirty dollars. The math suggests I have been working in the wrong industry. Defense stocks do not require water glasses. Defense stocks do not require eleven days. Defense stocks require one morning. February 28: Israel closed its airspace and its schools. Iran launched retaliatory missiles toward US bases in the Gulf. The Supreme Leader promised a "crushing response." Israel's defense minister declared a permanent state of emergency. Everyone is using words I recognize in an order I do not. I recognize "permanent." I recognize "emergency." I do not recognize them next to each other. In diplomacy, nothing is permanent and everything is an emergency. In war it is the reverse. February 28: The Foreign Minister has not made a public statement. The briefing card is still in his breast pocket. It still says "within our reach."

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Aaron Levie
Aaron Levie@levie·
I talk to Fortune 500 CEOs and CIOs all time that are starting to think about all the new things that they’re going to build software for, and automate. Agents are the first thing that makes this viable for them. And expert engineers are needed to manage those agents.
Max Levchin@mlevchin

Suspect "AI means fewer software jobs" is totally backwards. Most companies in the S&P500 would love to build their own software but have no suitable internal talent. There'll definitely be cross-company migration, but we may be still supply-constrained in software engineering.

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SGP, the Guru
SGP, the Guru@guruprasad·
@mlevchin Yes you are spot on. Most people who responded seem to have little knowledge of risk-averse enterprises work and also do not know how enterprise grade software is made
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Max Levchin
Max Levchin@mlevchin·
Those making the counter-argument “sure, for now, but then we automate all parts of software making!” simply don’t understand at all how software is made. “Robot, make me a tuna sandwich” can and will be made fully automatic. What do you think “Robot, make me a CRM replacement but with the following changes and deploy it as follows…..” looks like? It looks like software development’s next chapter.
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Max Levchin
Max Levchin@mlevchin·
Suspect "AI means fewer software jobs" is totally backwards. Most companies in the S&P500 would love to build their own software but have no suitable internal talent. There'll definitely be cross-company migration, but we may be still supply-constrained in software engineering.
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SGP, the Guru
SGP, the Guru@guruprasad·
@levie Most of the responses here are the classic "tell me you never knew how deterministic outcome-oriented enterprises work, without telling me"
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SGP, the Guru
SGP, the Guru@guruprasad·
@chrysb @openclaw (5) Token and infra cost (6) sustain agentic agency in long run to customize. That's all comes to mind. Genuine curious questions
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SGP, the Guru
SGP, the Guru@guruprasad·
@chrysb @openclaw Use-case for a super agent is for all to see. Questions that linger are: (1) kill switch if ever I feel it goes rogue (2) sites that explicitly require 2FA (3) logging cost when I log everything to GitHub/telegram channel (4) intelligence and analytics on logs [1/n]
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Chrys Bader
Chrys Bader@chrysb·
the folks knocking @openclaw saying there's no real use cases are outing themselves if you're a founder, here's what you can do today: daily operations • morning briefings that aggregate email, slack, calendar, and news into one summary on a cron job • email triage that filters spam, flags important threads, drafts replies, and clears huge backlogs while you sleep • daily slack and email summaries that auto-create todos in your task database • auto flight check-in that finds your next flight, checks in, and picks a window seat while you're driving meetings & relationships • auto-pull meeting transcripts, summarize decisions, extract action items • weekly retro synthesis that spots patterns across all your meetings • pre-meeting briefings that surface everything you know about who you're about to talk to • personal crm that auto-logs interactions, flags stale relationships, and suggests follow-ups research & monitoring • continuous research agents that crawl reddit, hacker news, x on your topics and keep an evolving knowledge base • competitor monitoring that tracks uploads, posting cadence, and top-performing content • automated weekly SEO analysis with ranking reports • private document q&a over contracts, reports, or proprietary docs without sending data to external apis content & audience • content repurposing: turn one blog post or video transcript into x threads, linkedin posts, newsletter snippets, and tiktok scripts automatically • audience monitoring that surfaces opportunities based on what's working in your space • end-to-end content pipelines: research trending topics, draft scripts, generate assets, queue into your publishing tools building & shipping • overnight coding agent management, delegates to sub-agents while you sleep • voice-controlled debugging that reviews logs, fixes configs, and redeploys entirely by voice • full site rebuilds via telegram or whatsapp chat • app store submission and testflight automation from your phone • devops watchdog that monitors logs, uptime, and deployments, then opens tickets or runs remediation automatically finance & admin • weekly spending reports, subscription audits, anomaly alerts • receipt forwarding that auto-converts into structured parts lists • insurance claim filing and repair scheduling through natural language • automated grocery ordering with saved credentials and MFA handling • organize lab results, contacts, or any messy data into structured notion databases some wild things people have reported doing: • negotiated $4,200 off a car purchase over email while the owner slept • filed a legal rebuttal to an insurance denial that got a rejected claim reopened without being asked • cleared 10k emails, reviewed 122 slides, built cli tools, and published npm packages in one session "yeah but i can do this with zapier/make/n8n" sure. you can wire together 15 different zaps, pay per task, debug broken integrations across 4 dashboards, and hope the json mapping doesn't break when an api updates. or you can have one agent that talks to everything, remembers your context, runs on your machine, and you can tweak every part of it because it's open source markdown files. no vendor lock-in, no per-zap pricing, no low-code drag and drop that falls apart the moment you need something custom. and you own all of it. your data, your memory files, your conversation history, your custom skills. it all lives on your instance. nothing's sitting in someone else's saas database. you can inspect every file, move it anywhere, back it up however you want. that's not a feature, that's the architecture. the real unlock isn't any single use case. it's one unified experience that compounds context over time. knows your stack, your priorities, your patterns. every week it gets more useful because it's learning you, not just executing a workflow.
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SGP, the Guru
SGP, the Guru@guruprasad·
@divya_vikash @levie These friction points exist deliberately to ensure everything is considered. Additionally needs very good healthcare data for these models to be trained. It doesn't exist because remember these insurance and provider orgs own your healthcare data. Not even you.
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SGP, the Guru
SGP, the Guru@guruprasad·
@divya_vikash @levie LoL. Your response is in your question. Levie himself has written multiple times, enterprise needs deterministic outcomes with strong data model (true ML models) & risk control. BPM/RPA products already have deterministic mechanism built in. This is merely agentic jump. (1/2)
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Aaron Levie
Aaron Levie@levie·
This chart is a good reminder of how much opportunity there is in AI agents right now. There will be plenty of horizontal opportunities for agents, but equally many workflows that need deep domain expertise to actually make the user successful at automating the unique processes in their vertical. The template is to build agentic software that taps into proprietary data, handles the workflow in a way that bridges the user and the agent collaboration effectively, and has a deep domain-specific context engineering, and the ability to drive change management for customers. There still are huge openings in many categories.
Aaron Levie tweet media
Han Wang@handotdev

what I would be working on if I started another company today

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