Technical16:9 - 9 slides
Engineering Deep Dive
A system-design walkthrough for tech talks and internal reviews. Architecture diagrams on the left, tradeoffs on the right, code where it counts.
Best for
Conference talks, internal architecture reviews, and onboarding sessions where the audience is technical and wants the real details, not a marketing version.
Slide preview
Slide 1 - title
Engineering Deep Dive
- System name
- Your name, team
Slide 2 - content
The problem we were solving
- Workload shape
- Constraints: latency, throughput, cost
- What we ruled out
Slide 3 - split
Architecture at a glance
- Request path
- Storage layer
- Async path
Slide 4 - content
The hot path
- Step 1 - ingress
- Step 2 - validation
- Step 3 - write
- Step 4 - fanout
Slide 5 - split
The storage decision
- Option A - Postgres
- Option B - Dynamo
- Why we picked B
Slide 6 - code
The query that matters
- SELECT id, payload FROM events
- WHERE user_id = $1 AND ts > now() - interval '1 hour'
- ORDER BY ts DESC LIMIT 100;
Slide 7 - content
Tradeoffs we accepted
- Eventual consistency on the read replica
- Higher write amplification
- Simpler ops
Slide 8 - content
What we would do differently
- Ship the read replica earlier
- Instrument from day one
- Do not hand-roll the queue
Slide 9 - title
Questions
- Thanks - name@company.com
The template
The full deck JSON. Copy it, or open it directly in the visual slides editor to edit on a real tldraw canvas and export PPTX.
deck.json
{
"slug": "engineering-deep-dive",
"name": "Engineering Deep Dive",
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"description": "A system-design walkthrough for tech talks and internal reviews. Architecture diagrams on the left, tradeoffs on the right, code where it counts.",
"bestFor": "Conference talks, internal architecture reviews, and onboarding sessions where the audience is technical and wants the real details, not a marketing version.",
"aspect": "16:9",
"accent": "#0a0a0a",
"slides": [
{
"title": "Engineering Deep Dive",
"bullets": [
"System name",
"Your name, team"
],
"layout": "title"
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{
"title": "The problem we were solving",
"bullets": [
"Workload shape",
"Constraints: latency, throughput, cost",
"What we ruled out"
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{
"title": "Architecture at a glance",
"bullets": [
"Request path",
"Storage layer",
"Async path"
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{
"title": "The hot path",
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"Step 1 - ingress",
"Step 2 - validation",
"Step 3 - write",
"Step 4 - fanout"
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{
"title": "The storage decision",
"bullets": [
"Option A - Postgres",
"Option B - Dynamo",
"Why we picked B"
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},
{
"title": "The query that matters",
"bullets": [
"SELECT id, payload FROM events",
"WHERE user_id = $1 AND ts > now() - interval '1 hour'",
"ORDER BY ts DESC LIMIT 100;"
],
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{
"title": "Tradeoffs we accepted",
"bullets": [
"Eventual consistency on the read replica",
"Higher write amplification",
"Simpler ops"
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{
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"Ship the read replica earlier",
"Instrument from day one",
"Do not hand-roll the queue"
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"Thanks - name@company.com"
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