I love this! I use coding agents to generate web-based slide decks where “master slides” are just components, and we already have rules + assets to enforce corporate identity. With content + prompts, it’s straightforward to generate a clean, predefined presentation.
What I’d really want on top is an “improv mode”: during the talk, I can branch off based on audience questions or small wording changes, and the system proposes (say) 3 candidate next slides in real time. I pick one, present it, then smoothly merge back into the main deck.
Example: if I mention a recent news article / study / paper, it automatically generates a slide that includes a screenshot + a QR code link to the source, then routes me back to the original storyline.
With realtime voice + realtime code generation, this could turn the boring old presenter view into something genuinely useful.
GPT‑5.3‑Codex‑Spark
41–50 of 415 posts
Re: GPT‑5.3‑Codex‑Spark
#42> Today, we’re releasing a research preview of GPT‑5.3-Codex-Spark, a smaller version of GPT‑5.3-Codex, and our first model designed for real-time coding. Codex-Spark marks the first milestone in our partnership with Cerebras, which we announced in January .
Nevermind. [0]
Re: GPT‑5.3‑Codex‑Spark
#43> Our latest frontier models have shown particular strengths in their ability to do long-running tasks, working autonomously for hours, days or weeks without intervention. I have yet to see this (produce anything actually useful).
How hard have you tried?
I've been finding that the Opus 4.5/4.6 and GPT-5.2/5.3 models really have represented a step-change in how good they are at running long tasks.
I can one-shot prompt all sorts of useful coding challenges now that previously I would have expected to need multiple follow-ups to fix mistakes the agents made.
I got all of this from a single prompt, for example: https://github.com/simonw/research/tree/main/cysqlite-wasm-w... - including this demo page: https://simonw.github.io/research/cysqlite-wasm-wheel/demo.h... - using this single prompt: https://github.com/simonw/research/pull/79
Re: GPT‑5.3‑Codex‑Spark
#44This is closer to 5.1 mini it seems and tied to Pro account. GLM 4.7 is available on-demand on Cerebras today [1] and performs better and cheaper... [1] https://www.cerebras.ai/blog/glm-4-7
GLM 4.7 scores 41.0% on Terminal Bench 2.0 [1] compared to 58.4% for GPT-5.3-Codex-Spark [2].
[1] https://z.ai/blog/glm-4.7 [2] https://openai.com/index/introducing-gpt-5-3-codex-spark/
Re: GPT‑5.3‑Codex‑Spark
#45Is this the first time one of the big 3 using Cerebras? I've been waiting for this day...
They were afraid for the untested tech but it looks like a leap in speed now
This is nonsense what do you mean? Mistral uses Cerebras for their LLMs as well. [0]
It's certainly not "untested".
Re: GPT‑5.3‑Codex‑Spark
#46> Our latest frontier models have shown particular strengths in their ability to do long-running tasks, working autonomously for hours, days or weeks without intervention. I have yet to see this (produce anything actually useful).
It worked for me several times.
It's easy to say that these increasingly popular tools are only able to produce useless junk. You haven't tried, or you haven't "closed the loop" so that the agent can evaluate its own progress toward acceptance criteria, or you are monitoring incompetent feeds of other users.
Re: GPT‑5.3‑Codex‑Spark
#47> Our latest frontier models have shown particular strengths in their ability to do long-running tasks, working autonomously for hours, days or weeks without intervention. I have yet to see this (produce anything actually useful).
I routinely leave codex running for a few hours overnight to debug stuff If you have a deterministic unit test that can reproduce the bug through your app front door, but you have no idea how the bug is actually happening, having a coding agent just grind through the slog of sticking debug prints everywhere, testing hypotheses, etc — it's an ideal usecase
How can you afford that?
Re: GPT‑5.3‑Codex‑Spark
#48Your move, Anthropic. (Yes I know they released /fast last week but I’m loving the constant oneupsmanship)
Re: GPT‑5.3‑Codex‑Spark
#49> Our latest frontier models have shown particular strengths in their ability to do long-running tasks, working autonomously for hours, days or weeks without intervention. I have yet to see this (produce anything actually useful).
How hard have you tried? I've been finding that the Opus 4.5/4.6 and GPT-5.2/5.3 models really have represented a step-change in how good they are at running long tasks. I can one-shot prompt all sorts of useful coding challenges now that previously I would have expected to need multiple follow-ups to fix mistakes the agents made. I got all of this from a single prompt, for example: https://github.com/simonw/research…
What do you mean? The generated script just downloads the sources and runs pyodide: https://github.com/simonw/research/blob/main/cysqlite-wasm-w...
There is maybe 5 relevant lines in the script and nothing complex at all that would require to run for days.