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Engineering teams require focus now more than ever. We’ve changed the way we solve for paper cuts in the product while maintaining our speed of shipping: "The second [a bug] comes through Slack it triggers an agent that figures out the right team to send it to. That team’s... show more

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Your engineering team is about to snap. And your AI coding agent is making it worse. Introducing CodeRabbit Agent for Slack 🎉 A second brain for engineering teams. Because your tribal knowledge lives in Slack threads nobody can find. At CodeRabbit, we review millions of PRs every week and know how ace engineering teams operate on the planet. The same three things slow every team we see: - Context and decisions that live elsewhere. - Lack of a team-level durable knowledge base - And a trust layer that gives a safety net to your teams Built for Agentic SDLC workflows, CodeRabbit Agent for Slack solves all three problems in one shot while enabling teams to collaborate in real-time with the Agent. CodeRabbit Agent is Slack-native and builds your team’s operating context from every thread, every decision, every conversation your team has ever had. Make your team’s context compound!

Your engineering team is about to snap. And your AI coding agent is making it worse. Introducing CodeRabbit Agent for Slack 🎉 A second brain for engineering teams. Because your tribal knowledge lives in Slack threads nobody can find. At CodeRabbit, we review millions of PRs every week and know how ace engineering teams operate on the planet. The same three things slow every team we see: - Context and decisions that live elsewhere. - Lack of a team-level durable knowledge base - And a trust layer that gives a safety net to your teams Built for Agentic SDLC workflows, CodeRabbit Agent for Slack solves all three problems in one shot while enabling teams to collaborate in real-time with the Agent. CodeRabbit Agent is Slack-native and builds your team’s operating context from every thread, every decision, every conversation your team has ever had. Make your team’s context compound!

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The CTO of a $1.5B agent-native software company says we're moving towards a world where the entire team builds the product engineering system that powers your product instead of directly working on the product. They will modify the agents and the constitution of the agents to help them prioritize tasks per Eno Reyes. They will also modify the review system so that it reviews more accurately. It will be akin to a dark factory where the lights are off because it's all robots with no humans inside. In that world, there will be way more things for humans to be involved in because the debates around prioritization/product will be harder and require stronger judgment.

The CTO of a $1.5B agent-native software company says we're moving towards a world where the entire team builds the product engineering system that powers your product instead of directly working on the product. They will modify the agents and the constitution of the agents to help them prioritize tasks per Eno Reyes. They will also modify the review system so that it reviews more accurately. It will be akin to a dark factory where the lights are off because it's all robots with no humans inside. In that world, there will be way more things for humans to be involved in because the debates around prioritization/product will be harder and require stronger judgment.

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A 2-person startup crossed $2M ARR with an AI agent doing the work of an ops hire. The agent was given read-only access to their codebase and database along with connected tools like Intercom, Stripe, CRM, and Fathom through CLIs. They routed Slack, email, and support requests into a task queue so the agent could pick up each task and run it in Claude Code. So when a customer asked about billing or product behavior, it could inspect how the business actually worked. Along with these tools, a coding agent was also provided. When the ops agent found a repeated task it could not do yet, the coding agent built a tool for it. That tool became permanent. Over time, this grew to 45+ internal tools. The agent also had an instruction.md where it stored the co-founder's feedback to avoid repeating its mistakes.

A 2-person startup crossed $2M ARR with an AI agent doing the work of an ops hire. The agent was given read-only access to their codebase and database along with connected tools like Intercom, Stripe, CRM, and Fathom through CLIs. They routed Slack, email, and support requests into a task queue so the agent could pick up each task and run it in Claude Code. So when a customer asked about billing or product behavior, it could inspect how the business actually worked. Along with these tools, a coding agent was also provided. When the ops agent found a repeated task it could not do yet, the coding agent built a tool for it. That tool became permanent. Over time, this grew to 45+ internal tools. The agent also had an instruction.md where it stored the co-founder's feedback to avoid repeating its mistakes.

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Cursor pays engineers $1,100,000 a year to run teams of AI agents that ship code while they sleep. [The CEO of Cursor explained in 9 minutes how they ship at 100x speed using team of agents] ↓ Save this before everyone copies the playbook 1. Engineers no longer babysit one assistant. They manage dozens of agent colleagues working in parallel, each on its own remote machine 2. Validation contract before code, not after. Humans only at scoping and review. 3. The agent team handles the full loop : planning, coding, testing, shipping PRs with each agent specialised for a role. Watch the guide. Then read the guide below by Khairallah AL-Awady

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Jeff Bezos explains the idea of “paper cut” teams “There are big things that are really important to manage — and by the way, it’s astonishingly hard to focus on just the big things. Even though they’re obvious, they’re really hard to focus on. But in addition to that, there are all these tiny customer deficiencies. We call those ‘paper cuts,’ and we make long lists of them. Then we have dedicated teams that go fix paper cuts. That’s because the teams that are working on the big issues never get to the paper cuts. They never work their way down the list. They’re working on big things — as they should and as you want them to — so you need special teams who are charged with fixing paper cuts.” Video source: Lex Fridman (2023)

Jeff Bezos explains the idea of “paper cut” teams “There are big things that are really important to manage — and by the way, it’s astonishingly hard to focus on just the big things. Even though they’re obvious, they’re really hard to focus on. But in addition to that, there are all these tiny customer deficiencies. We call those ‘paper cuts,’ and we make long lists of them. Then we have dedicated teams that go fix paper cuts. That’s because the teams that are working on the big issues never get to the paper cuts. They never work their way down the list. They’re working on big things — as they should and as you want them to — so you need special teams who are charged with fixing paper cuts.” Video source: Lex Fridman (2023)

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Elon Musk believes that YES, prominent Democrats like Maxine Waters, Adam Schiff and Chuck Schumer have received USAID money funneled through NGOs “There is a massive amount of corruption — So they'll send the money overseas to one NGO, then it'll go through a bunch of them, and then I'm highly confident that a bunch of that money then comes back to the United States and lands in the pockets of the people you just mentioned.” “So what happens is there's money that, obviously it's your taxpayer money, that is then sent to various government organizations who then send it to, to NGOs, which, which an NGO is a non-governmental organization. But obviously if it's a government-funded non-governmental organization, it's just an organization, it's just a government. And effectively there's a giant fraud loophole, which is that the government can send money to an NGO that is then no longer governed by the law laws of the United States. So they'll, they'll send the money overseas to one NGO, then it'll go through a bunch of a bunch of them. And then I'm highly confident that a bunch of that money then comes back to the United States and lands in the pockets of the people you just mentioned. But it is a circuitous route. It's not like it doesn't go directly, but let's just say that there's a lot of strangely wealthy members of Congress where I'm trying to connect the dots of how did they become rich? Well earning, how'd they get $20 million if they're earning $200,000 a year? It sounds that's how, how do I just, nobody can explain that. So it’s something we're gonna try to figure it out and certainly stop it from happening. The whole NGO scam is just crazy — It’s blown my mind really”

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OpenAI just released Codex Security, an AI agent that scans software projects to fix vulnerabilities while ignoring harmless bugs. Testing on 1.2mn commits found 792 critical flaws and dropped false alarms by 50%. Here is how the Codex Security agent works Initially, it scans your software project to learn how all the different pieces of code connect. It uses that knowledge to build a threat model, which acts as a custom map showing exactly where your software might be exposed to hackers. The agent then hunts for potential security holes based on that specific map. When it spots a possible flaw, it does not just send you a random alert. Instead, it creates a completely safe and isolated copy of your system known as a sandbox. The agent then actively tries to break into that sandboxed copy to prove if the security weakness is a real danger. If the agent successfully exploits its own test environment, it knows the bug is a genuine threat and not a false alarm. After confirming the danger, the agent writes a custom software patch to fix the broken code. It then tests that new patch to guarantee the fix does not accidentally break any other features in your software.

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today we introduce a beta of Krea in Slack. expand your team’s creative work with the latest AI models and an agent that adapts to your preferences. try it now at krea . ai

today we introduce a beta of Krea in Slack. expand your team’s creative work with the latest AI models and an agent that adapts to your preferences. try it now at krea . ai

Krea

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ELON: “IT’S AN HONOR TO WORK WITH THE BEST ROCKET ENGINEERING TEAM EVER ASSEMBLED” “It’s like this, if this was a video game, it’s set to maximum difficulty, but not impossible. That’s where we are. It’s not as though others ignored the concept of reusability, they just concluded that it was too difficult to achieve. We’ve been working on this for a long time at SpaceX, and I’m the chief engineer of the company. We have an extremely talented engineering team, the best rocket engineering team ever assembled. It’s an honor to work with such incredible people.” Source: Elon Musk SpaceX

ELON: “IT’S AN HONOR TO WORK WITH THE BEST ROCKET ENGINEERING TEAM EVER ASSEMBLED” “It’s like this, if this was a video game, it’s set to maximum difficulty, but not impossible. That’s where we are. It’s not as though others ignored the concept of reusability, they just concluded that it was too difficult to achieve. We’ve been working on this for a long time at SpaceX, and I’m the chief engineer of the company. We have an extremely talented engineering team, the best rocket engineering team ever assembled. It’s an honor to work with such incredible people.” Source: Elon Musk SpaceX

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🇨🇳🇺🇸🇪🇺 People can tell the mentality level of a Chinese and an American or a European just by they way they talk, it was an amazing speech. But the Chinese have changed. We used to go out of our way to debunk the anti-China media and trolls' lies. Now? Who gives a damn? We’ll keep building our future while they keep yapping like a bunch of powerless clowns.

🇨🇳🇺🇸🇪🇺 People can tell the mentality level of a Chinese and an American or a European just by they way they talk, it was an amazing speech. But the Chinese have changed. We used to go out of our way to debunk the anti-China media and trolls' lies. Now? Who gives a damn? We’ll keep building our future while they keep yapping like a bunch of powerless clowns.

𝘊𝘰𝘳𝘳𝘪𝘯𝘦

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Today, we launched our official Claude connector at Quo (formerly OpenPhone). Now you can get insights from every customer conversation, send bulk messages, update contacts, and so much more - all directly inside Claude. I've been using this every day to understand how things are going for our inbound sales team, what's working with prospects, and where the coaching opportunities are. With the Claude connector, I create a scheduled task that scores all the transcripts from our Quo phone number against 2 of our sales rubrics and outputs a report with a summary, score, and any coaching opportunities. Let's be honest, no manager has time to listen to and score 50 calls a day. But Claude does. Now I just check Slack every morning, where Claude delivers all the context I need. Every Quo customer with Claude now has this capability (and so much more). Connecting the tools takes minutes, and then work that used to require an Engineering team is only a prompt away. Huge shout-out to everyone on our team for shipping this! I can't wait to see what you build with it.

Today, we launched our official Claude connector at Quo (formerly OpenPhone). Now you can get insights from every customer conversation, send bulk messages, update contacts, and so much more - all directly inside Claude. I've been using this every day to understand how things are going for our inbound sales team, what's working with prospects, and where the coaching opportunities are. With the Claude connector, I create a scheduled task that scores all the transcripts from our Quo phone number against 2 of our sales rubrics and outputs a report with a summary, score, and any coaching opportunities. Let's be honest, no manager has time to listen to and score 50 calls a day. But Claude does. Now I just check Slack every morning, where Claude delivers all the context I need. Every Quo customer with Claude now has this capability (and so much more). Connecting the tools takes minutes, and then work that used to require an Engineering team is only a prompt away. Huge shout-out to everyone on our team for shipping this! I can't wait to see what you build with it.

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At Postman, we have adopted an AI-native mindset to product development. What does this mean in practice? Just like you can generate text with AI, Postman's Agent Mode can generate a UI as well. Case in point: we have added the ability to review, generate, and change diffs for important changes right inside agent mode's chat interaction. If the user trusts agent mode, they can continue in auto-mode, but for critical changes, they can have the agent mode inform the user, review what is changing, and then give the go ahead to approve. See this in action below in the video! While there is a lot of focus on AI generated code today, I believe a large chunk of pre-built UI work will just go away and micro-interactions and workflow steps will be created on the fly through a combination of AI + APIs. How to operate in this new world? Build your API first. Hook it up to AI. If your users really want the UI every time, invest in the GUI.

At Postman, we have adopted an AI-native mindset to product development. What does this mean in practice? Just like you can generate text with AI, Postman's Agent Mode can generate a UI as well. Case in point: we have added the ability to review, generate, and change diffs for important changes right inside agent mode's chat interaction. If the user trusts agent mode, they can continue in auto-mode, but for critical changes, they can have the agent mode inform the user, review what is changing, and then give the go ahead to approve. See this in action below in the video! While there is a lot of focus on AI generated code today, I believe a large chunk of pre-built UI work will just go away and micro-interactions and workflow steps will be created on the fly through a combination of AI + APIs. How to operate in this new world? Build your API first. Hook it up to AI. If your users really want the UI every time, invest in the GUI.

Abhinav Asthana

104,263 Aufrufe • vor 1 Jahr

Anthropic co-founder Ben Mann has the clearest definition of AGI I've heard, which he calls The Economic Turing Test: "If you contract an agent for 1-3 months on a particular job and it turns out to be a machine rather than a person, then it's passed the Economic Turing Test for that role. And if the agent can pass that test for 50% of money-weighted jobs, then we have transformative AI. If we pass that threshold, then we would expect massive effects on world GDP increases, and societal change, and the number of people that are employed once these things are possible. That's the start of a new era."

Anthropic co-founder Ben Mann has the clearest definition of AGI I've heard, which he calls The Economic Turing Test: "If you contract an agent for 1-3 months on a particular job and it turns out to be a machine rather than a person, then it's passed the Economic Turing Test for that role. And if the agent can pass that test for 50% of money-weighted jobs, then we have transformative AI. If we pass that threshold, then we would expect massive effects on world GDP increases, and societal change, and the number of people that are employed once these things are possible. That's the start of a new era."

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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.

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.

Bret Taylor

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ANTHROPIC SPENT $2.3M ON A LOOP MANUAL WITH 7 PRINCIPLES THAT TURN AN AGENT INTO A MULTI-TASK ASSISTANT 4 years of development and 1000+ hours of lectures - now anyone can launch an agent that earns instead of falls Simplicity → Tool Design → Evaluation → Disclosure → Orchestration → Stop Conditions start with the simplest solution - one call x1, workflow x4, agent x15 - most tasks never needed an agent at all 60% of failures come from a tool written vaguely - clear parameters complete the task that vague ones stop the agent generates, grades itself and returns with notes if wrong - without this the first answer is always the final one 50 tools in context and the agent gets confused - give it 3 relevant ones and it completes the task Opus 5 plans, Fable 5 executes in parallel - parallelism wins only when subtasks do not depend on each other without a turn limit the agent can burn $10,000 overnight and you find out in the morning when nothing can be changed bookmark & paste into Claude Code today - tomorrow the agent earns instead of falls

ANTHROPIC SPENT $2.3M ON A LOOP MANUAL WITH 7 PRINCIPLES THAT TURN AN AGENT INTO A MULTI-TASK ASSISTANT 4 years of development and 1000+ hours of lectures - now anyone can launch an agent that earns instead of falls Simplicity → Tool Design → Evaluation → Disclosure → Orchestration → Stop Conditions start with the simplest solution - one call x1, workflow x4, agent x15 - most tasks never needed an agent at all 60% of failures come from a tool written vaguely - clear parameters complete the task that vague ones stop the agent generates, grades itself and returns with notes if wrong - without this the first answer is always the final one 50 tools in context and the agent gets confused - give it 3 relevant ones and it completes the task Opus 5 plans, Fable 5 executes in parallel - parallelism wins only when subtasks do not depend on each other without a turn limit the agent can burn $10,000 overnight and you find out in the morning when nothing can be changed bookmark & paste into Claude Code today - tomorrow the agent earns instead of falls

Sprytix

27,543 Aufrufe • vor 16 Tagen

"Orgs and cos building MCP servers are taking an LLM-first approach to what the API needs to expose to the agent(s)." - Nikunj Handa from OpenAI "For example, Stripe has a bunch of APIs that can be used to create a subscription/customer/product/price. For an LLM, it can just combine that into a single function." "Instead of returning this massive JSON object, they can return something very specific to the task being solved, so that the LLM can more easily understand what's happening." "It's an opportunity to rewrite your APIs to be very LLM-first. Why do 2 hours of work, when you can do it in 4 lines of code under a minute?"

"Orgs and cos building MCP servers are taking an LLM-first approach to what the API needs to expose to the agent(s)." - Nikunj Handa from OpenAI "For example, Stripe has a bunch of APIs that can be used to create a subscription/customer/product/price. For an LLM, it can just combine that into a single function." "Instead of returning this massive JSON object, they can return something very specific to the task being solved, so that the LLM can more easily understand what's happening." "It's an opportunity to rewrite your APIs to be very LLM-first. Why do 2 hours of work, when you can do it in 4 lines of code under a minute?"

TBPN

11,445 Aufrufe • vor 1 Jahr

SPEC IS BECOMING THE PRODUCT An Anthropic engineer gave Claude a spec, pointed it to an Asana board and left for the weekend. Claude broke it into tickets and spun up a team of agents. The agents started picking up tasks on their own. No one told them to. They just did.

SPEC IS BECOMING THE PRODUCT An Anthropic engineer gave Claude a spec, pointed it to an Asana board and left for the weekend. Claude broke it into tickets and spun up a team of agents. The agents started picking up tasks on their own. No one told them to. They just did.

Shubham Saboo

285,667 Aufrufe • vor 5 Monaten

well thats fucking it - anthropic has officially replaced software engineers. claude is now a 24 hr autonomous coding agent. claude can now operate your entire computer and CLAUDE CODE = end-to-end software engineering: - claude writes the code for you - then literally opens the app it coded - clicks through the entire app and find bugs - then fixes the bugs and improves the app in hours. previously claude generated code, you run it and give claude feedback. thats completely gone now. all in a continuous loop without leaving your terminal 😂 we're barely through monday. well done lol

well thats fucking it - anthropic has officially replaced software engineers. claude is now a 24 hr autonomous coding agent. claude can now operate your entire computer and CLAUDE CODE = end-to-end software engineering: - claude writes the code for you - then literally opens the app it coded - clicks through the entire app and find bugs - then fixes the bugs and improves the app in hours. previously claude generated code, you run it and give claude feedback. thats completely gone now. all in a continuous loop without leaving your terminal 😂 we're barely through monday. well done lol

Ejaaz

1,156,741 Aufrufe • vor 4 Monaten

$ANTHROPIC JUST QUIETLY SHIPPED A FEATURE THAT LETS CLAUDE SPAWN A WHOLE TEAM OF AGENTS THAT MESSAGE EACH OTHER AND REVIEW EACH OTHER'S WORK. It's a Claude Code feature called agent teams. The team lead spawns multiple agents that share a task list and message each other directly, not subagents reporting back, actual peers. In the demo a QA agent caught three bugs, sent the work back to the front-end and back-end devs, they fixed it, app shipped in one pass. How to run it: 1. Enable it. Needs Claude Code v2.1.32+. Add to settings.json: "env": { "CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS": "1" }. Or paste that to Claude and say "add this to my settings." Restart. 2. Prompt in plain English. Start with a goal (agents wake with zero context), then "create a team of 3 using Sonnet," describe each role, its deliverable, and who it messages when done. 3. The rules: each agent owns its own files, define exact outputs, name who talks to who, keep it to 3-5 agents. Use it for complex work with separate parts running in parallel. Skip it for simple or sequential tasks, teams cost 3-4x the tokens. Bookmark this.$

ANTHROPIC JUST QUIETLY SHIPPED A FEATURE THAT LETS CLAUDE SPAWN A WHOLE TEAM OF AGENTS THAT MESSAGE EACH OTHER AND REVIEW EACH OTHER'S WORK. It's a Claude Code feature called agent teams. The team lead spawns multiple agents that share a task list and message each other directly, not subagents reporting back, actual peers. In the demo a QA agent caught three bugs, sent the work back to the front-end and back-end devs, they fixed it, app shipped in one pass. How to run it: 1. Enable it. Needs Claude Code v2.1.32+. Add to settings.json: "env": { "CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS": "1" }. Or paste that to Claude and say "add this to my settings." Restart. 2. Prompt in plain English. Start with a goal (agents wake with zero context), then "create a team of 3 using Sonnet," describe each role, its deliverable, and who it messages when done. 3. The rules: each agent owns its own files, define exact outputs, name who talks to who, keep it to 3-5 agents. Use it for complex work with separate parts running in parallel. Skip it for simple or sequential tasks, teams cost 3-4x the tokens. Bookmark this.

Yarchi

461,138 Aufrufe • vor 1 Monat

Systematic literature reviews take 12-18 months to complete. Looks like AI is going to fully automate systematic reviews sooner than later. SciSpace ( SciSpace) just launched an autonomous AI agent that conducts a systematic literature review with a single prompt. Go to scispace[.]com and run the following prompt: "Conduct a systematic literature review on [your topic]" SciSpace agent will generate research questions based on the PICO framework. You can review these questions and edit them according to your specific requirements. The agent will also draft screening criteria that you can edit according to your needs. Then the agent asks you to select the databases you want to use and the date range for paper. After this step, everything is fully automated. The agent will search for papers in the relevant databases, it will combine and rerank the papers. Then it will start the title and abstract screening and include the papers that meet the include criteria. In the next step, it will download the full text of included papers and screen them followed by data extraction. Based on the extracted data, it generates a complete systematic literature review and also a PRISMA diagram. It will also give you a table of papers included along with the rational for including them. The only thing that is keeping AI agents to fully automate systematic literature reviews fields is the papers behind paywalls. Check out the agent at scispace[.]com and see if you find its review useful.

Systematic literature reviews take 12-18 months to complete. Looks like AI is going to fully automate systematic reviews sooner than later. SciSpace ( SciSpace) just launched an autonomous AI agent that conducts a systematic literature review with a single prompt. Go to scispace[.]com and run the following prompt: "Conduct a systematic literature review on [your topic]" SciSpace agent will generate research questions based on the PICO framework. You can review these questions and edit them according to your specific requirements. The agent will also draft screening criteria that you can edit according to your needs. Then the agent asks you to select the databases you want to use and the date range for paper. After this step, everything is fully automated. The agent will search for papers in the relevant databases, it will combine and rerank the papers. Then it will start the title and abstract screening and include the papers that meet the include criteria. In the next step, it will download the full text of included papers and screen them followed by data extraction. Based on the extracted data, it generates a complete systematic literature review and also a PRISMA diagram. It will also give you a table of papers included along with the rational for including them. The only thing that is keeping AI agents to fully automate systematic literature reviews fields is the papers behind paywalls. Check out the agent at scispace[.]com and see if you find its review useful.

Mushtaq Bilal, PhD

42,003 Aufrufe • vor 4 Monaten