IndyDevDan | Your AI Agents can SELF-CORRECT: Using Assistants API to AUTO FIX SQL Database Errors @indydevdan | Uploaded November 2023 | Updated October 2024, 1 hour ago.
ENHANCE YOUR SOFTWARE with SELF-CORRECTING AI Agents: A Deep Dive into Assistants API. Hey engineers and product builders. In this video we tap into self-correcting AI agents and see how they can auto correct issues that arise in software. This video provides a focused exploration of using Assistants API, coupled with GPT-4 Turbo, to create autonomous agents capable of identifying and fixing errors in software systems. We will start by looking at the current software architecture of our postgres data analytics tool then build a new code flow with a self correcting assistant built on top of Turbo4.
The upside of self-correcting agents in software engineering is pretty obvious. Save time, accomplish more while doing less, and worry less. It's a great step toward Agentic software engineering as a whole. Remember, we can't jump to step 10 and just 'build autonomous software'. We take small, sustainable steps the move us toward becoming true Agentic engineers. One experiment at a time. One application at a time. One product at a time. We'll also improve our Vite and Bun charged Vue.js front end with coding assistant AIDER running in the background while we tweak our Python/Flask backend. This is for software engineers and developers, this guide offers insights into enhancing software reliability and efficiency through AI-driven self-correction.
There's a lot of noise, drama and rapid news in the AI tech space right now and rightfully so. Focus going to be our most valuable tool in the age of AI.
Big shout out to everyone that's been staying focused, watching the channel, getting value, and taking their engineering and product building to the next level.
👍 THE CODEBASE
github.com/disler/multi-agent-postgres-data-analytics/tree/v9-self-correcting-assistant
💻 Talk to your database
talktoyourdatabase.com
🤖💻 AI Engineering Resources
LLM OS: youtube.com/watch?v=zjkBMFhNj_g
Assistants API: platform.openai.com/docs/assistants/how-it-works/objects
AI Pair Programming AIDER: https://aider.chat/
(1) Watch Part One
youtu.be/jmDMusirPKA
(2) Watch Part Two
youtu.be/JjVvYDPVrAQ
(3) Watch Part Three
youtu.be/4o8tymMQ5GM
(4) Watch Part Four
youtu.be/CKo-czvxFkY
(5) Watch Part Five
youtu.be/UA6IVMDPuC8
(6) Watch Part Six
youtu.be/XGCWyfA3rgQ
(7) Watch Part Seven
youtu.be/KwcrjP3vuy0
(8) Watch Part Eight
youtu.be/7EA19-D4-Zo
📘 Chapters
0:00 Diagnose, Generate, Execute
0:10 Tight Feedback Iteration Loops
0:20 LLMs can auto-correct any output system
0:33 Don't go all in on GPTs
0:53 Can LLMs run your software business?
1:30 Our Postgres Series is almost complete
1:50 Self Correcting Assistant - Recap
2:52 Firing off AIDER to work in parallel
4:25 Application Architecture - current and new
6:04 Channel 2024 Sneak Peek
6:25 Postgres Data Analytics Backend
7:22 An SQL query that will BOMB your database
8:21 New Self-Correcting Assistant Code
9:38 Turbo4 Assistants API wrapper class
14:35 Self-Correcting Assistant - RUN
16:11 Analyze the LLM corrected results
17:48 Agent Spyware Chat Conversation
18:20 Wow, it corrected a different error
19:25 All Great Devs have TIGHT feedback loops
20:45 Assistants API Pros, Cons, and Strategies
21:52 Build USE CASE specific AI Agents
22:35 The biggest WIN of the Assistants API
23:40 Assistants API is a heavy step forward
23:55 Negatives of Assistants API
25:47 Lot's of risk to our application
26:54 Should you go all in on Assistants API and GPTs?
28:00 A real world example of decided against Assistants API
28:42 Self-Correcting Assistants - Use Cases
29:15 The Channel has taken off but 2024 is going to be crazy
29:32 The End of the Series and what to expect
🐛 tags
#dataanalytics #agentic #promptengineering
ENHANCE YOUR SOFTWARE with SELF-CORRECTING AI Agents: A Deep Dive into Assistants API. Hey engineers and product builders. In this video we tap into self-correcting AI agents and see how they can auto correct issues that arise in software. This video provides a focused exploration of using Assistants API, coupled with GPT-4 Turbo, to create autonomous agents capable of identifying and fixing errors in software systems. We will start by looking at the current software architecture of our postgres data analytics tool then build a new code flow with a self correcting assistant built on top of Turbo4.
The upside of self-correcting agents in software engineering is pretty obvious. Save time, accomplish more while doing less, and worry less. It's a great step toward Agentic software engineering as a whole. Remember, we can't jump to step 10 and just 'build autonomous software'. We take small, sustainable steps the move us toward becoming true Agentic engineers. One experiment at a time. One application at a time. One product at a time. We'll also improve our Vite and Bun charged Vue.js front end with coding assistant AIDER running in the background while we tweak our Python/Flask backend. This is for software engineers and developers, this guide offers insights into enhancing software reliability and efficiency through AI-driven self-correction.
There's a lot of noise, drama and rapid news in the AI tech space right now and rightfully so. Focus going to be our most valuable tool in the age of AI.
Big shout out to everyone that's been staying focused, watching the channel, getting value, and taking their engineering and product building to the next level.
👍 THE CODEBASE
github.com/disler/multi-agent-postgres-data-analytics/tree/v9-self-correcting-assistant
💻 Talk to your database
talktoyourdatabase.com
🤖💻 AI Engineering Resources
LLM OS: youtube.com/watch?v=zjkBMFhNj_g
Assistants API: platform.openai.com/docs/assistants/how-it-works/objects
AI Pair Programming AIDER: https://aider.chat/
(1) Watch Part One
youtu.be/jmDMusirPKA
(2) Watch Part Two
youtu.be/JjVvYDPVrAQ
(3) Watch Part Three
youtu.be/4o8tymMQ5GM
(4) Watch Part Four
youtu.be/CKo-czvxFkY
(5) Watch Part Five
youtu.be/UA6IVMDPuC8
(6) Watch Part Six
youtu.be/XGCWyfA3rgQ
(7) Watch Part Seven
youtu.be/KwcrjP3vuy0
(8) Watch Part Eight
youtu.be/7EA19-D4-Zo
📘 Chapters
0:00 Diagnose, Generate, Execute
0:10 Tight Feedback Iteration Loops
0:20 LLMs can auto-correct any output system
0:33 Don't go all in on GPTs
0:53 Can LLMs run your software business?
1:30 Our Postgres Series is almost complete
1:50 Self Correcting Assistant - Recap
2:52 Firing off AIDER to work in parallel
4:25 Application Architecture - current and new
6:04 Channel 2024 Sneak Peek
6:25 Postgres Data Analytics Backend
7:22 An SQL query that will BOMB your database
8:21 New Self-Correcting Assistant Code
9:38 Turbo4 Assistants API wrapper class
14:35 Self-Correcting Assistant - RUN
16:11 Analyze the LLM corrected results
17:48 Agent Spyware Chat Conversation
18:20 Wow, it corrected a different error
19:25 All Great Devs have TIGHT feedback loops
20:45 Assistants API Pros, Cons, and Strategies
21:52 Build USE CASE specific AI Agents
22:35 The biggest WIN of the Assistants API
23:40 Assistants API is a heavy step forward
23:55 Negatives of Assistants API
25:47 Lot's of risk to our application
26:54 Should you go all in on Assistants API and GPTs?
28:00 A real world example of decided against Assistants API
28:42 Self-Correcting Assistants - Use Cases
29:15 The Channel has taken off but 2024 is going to be crazy
29:32 The End of the Series and what to expect
🐛 tags
#dataanalytics #agentic #promptengineering
