Category: intervals

The next interval session arrived on another hot evening. The planned structure was five 1,000 metre repetitions with jogging recoveries, but the main instruction was more important than the target pace: keep the efforts controlled and let the weather influence the speed.

At 29°C, this was not the evening to chase the fastest split of the training block.

The data

Metric	Result
Distance	Approximately 10.2 km
Time	1:02:38
Average pace	6:09/km
Average heart rate	142 bpm
Maximum heart rate	166 bpm
Average power	248 W
Elevation gain	53 m
Temperature	29°C, evening
Perceived effort	6 to 7/10

The faster sections felt controlled, and heart rate fell clearly during the recoveries. That recovery pattern mattered more than whether every repetition matched an exact pace.

The summary record does not preserve a separately confirmed list of interval splits, so this post cannot make precise claims about the consistency of all five repetitions. The reliable conclusion is that the workout structure was completed without the final effort becoming maximal.

What the coach saw

ChatGPT rated the session as a successful progression from the previous week. The total distance returned above ten kilometres, maximum heart rate stayed below the planned ceiling and perceived effort remained at 6 to 7 rather than drifting to 9 or 10.

The average values are not especially useful on their own because warm-up, recoveries and cool-down are included. The clearer signals were the repeated rises and falls in heart rate and the absence of a late loss of control.

The heat adjustment also worked. A fixed pace target could have turned the final repetitions into a race. Using effort and heart rate kept the training stimulus without adding avoidable exhaustion.

What changed next

Thursday stayed completely easy, with pace treated as irrelevant. The weekend still contained a tempo run followed by a long run, so there was no reason to make the recovery run faster.

This session did not produce a dramatic breakthrough. It showed something more useful for half marathon training: a hard workout can finish with the feeling that another repetition might have been possible.

Two days after the long run I was not supposed to do, the plan returned to interval work. The original session called for six 1,000 metre repetitions, but the conditions and the accumulated load made that target too ambitious.

It was 30°C and humid. The sensible version of the workout was four repetitions, with the emphasis on control rather than completing the number written in the first draft.

The data

Metric	Result
Distance	Approximately 8.5 km
Time	52:08
Average pace	6:08/km
Average heart rate	140 bpm
Maximum heart rate	168 bpm
Average power	249 W
Maximum power	399 W
Elevation gain	43 m
Temperature	30°C, humid
Perceived effort	7/10

The fastest recorded section was approximately 5:14/km. The complete split list is not available in the training record, so there is no value in inventing a neat progression that may not have happened.

What is clear is that the four faster blocks were completed and the overall session stayed below an all-out effort.

What the coach saw

ChatGPT treated the shorter session as the correct adjustment, not as a failed attempt at six repetitions. Heat raises the cardiovascular cost of the same pace, and the 19 kilometre run on Sunday was still close enough to matter.

The maximum heart rate of 168 bpm showed that the workout still reached the intended intensity. Adding two more repetitions simply to satisfy the original plan would have increased fatigue without proving anything useful.

The important decision was to preserve the purpose of the session: several controlled faster efforts, recoveries that allowed the heart rate to fall and enough restraint to train again later in the week.

What changed next

Thursday remained an easy run with no strides. The goal was to see whether the legs recovered normally after the heat session.

The Saturday tempo run was no longer automatic. It would depend on how the easy run felt, not just whether its average heart rate looked good.

This was a small but important correction to the coaching process. A plan should define the training stimulus. It should not turn the original repetition count into a test of obedience.

The next quality session consisted of five 1,000 metre repetitions with jogging recoveries.

The temperature was 28°C. I completed all five repetitions and rated the session 7.5 out of 10. It was hard, but not an all out effort.

The data

Metric	Result
Distance	Approximately 10.3 km
Time	1:01:39
Average pace	5:59/km
Average heart rate	142 bpm
Maximum heart rate	167 bpm
Average power	253 W
Maximum power	346 W
Elevation gain	9 m
Temperature	28°C
Perceived effort	7.5/10

The five faster blocks were clearly visible in the heart rate and power data. Heart rate climbed into the 150 to 165 bpm range during the repetitions and dropped during the recoveries.

There was no dramatic cardiovascular collapse. The final repetition was difficult, but the overall structure remained intact.

What the coach saw

ChatGPT considered the workout a successful quality session. Completing all five repetitions with jogging recoveries created a higher training density than walking or stopping between efforts.

The heat was again treated as an additional load. The coach did not interpret the average pace as a direct measure of what I could do in cooler conditions.

The next run was reduced to a genuinely easy 8 kilometres. The planned tempo run later in the week was also capped rather than extended.

The part the workout data did not explain

About an hour after finishing, I began to feel nauseous. I had eaten very little before the session.

The likely combination was heat, fluid and salt loss, and insufficient energy intake. I cooled down indoors, drank slowly and ate a small amount of easily digestible food.

This became a practical lesson for future quality sessions. Hard running in hot weather is not the right time to test how little food I can get away with.

The coach recommended a small carbohydrate based meal or snack before demanding workouts, followed by fluids, carbohydrate and protein afterwards.

The interval session itself was good. The preparation around it was not.

The plan called for a longer tempo session. I warmed up, ran a sustained faster block and then cooled down. The route was not flat, and the temperature had climbed back to 26°C.

By the end of the tempo section, I felt close to my limit.

The data

Metric	Result
Distance	Approximately 11.0 km
Time	1:04:58
Average pace	5:54/km
Average heart rate	145 bpm
Maximum heart rate	169 bpm
Average power	257 W
Elevation gain	64 m
Temperature	26°C
Perceived effort	7/10

The tempo block covered roughly seven kilometres. Pace varied between about 5:05 and 5:40 per kilometre, partly because of the hills. Heart rate rose gradually through the block and reached the high 160s near the end.

Was it really the limit?

ChatGPT challenged my description of the run. I had said that I reached my performance limit, but I also rated the session 7 out of 10.

Those two statements do not quite match. A true maximum effort would normally be closer to 9 or 10. The data looked more like a hard threshold session that remained under control.

I think that is fair. The final part felt very hard, but I was still able to cool down properly. I had not emptied the tank completely.

What the coach saw

The coach liked the duration of the faster block and the fact that there was no sudden collapse in pace or power. It also noted that the hills made pace a poor guide. A flatter route, or a stronger focus on power and effort, would make future tempo runs easier to control.

The target half marathon pace for a finish around 1:54 is close to 5:24/km. I had already run around or faster than that pace for substantial parts of this workout, but not yet for anything close to race distance.

What came next

The following day’s long run was deliberately kept easy. There would be no fast finish. If my legs felt heavy in the morning, the distance could be shortened.

This was one of the tougher decisions in the plan. Running long on tired legs can be useful, but only if the long run does not become a second hard workout.

I returned to the same route I had used the previous week. This time the temperature was 21°C instead of 28°C.

The difference was immediate. The run felt better, and the numbers improved with it.

The data

Metric	Previous comparable run	This run
Temperature	28°C	21°C
Average pace	6:38/km	6:12/km
Average heart rate	135 bpm	143 bpm
Average power	235 W	249 W
Maximum heart rate	164 bpm	168 bpm
How it felt	Controlled	Good

I ran 26 seconds per kilometre faster and produced 13 more watts on average. Heart rate rose, as it should have at the higher intensity, but the effort still felt manageable.

What the coach saw

ChatGPT called it my best faster session of the previous few weeks. Not because the pace was spectacular, but because pace, power, heart rate and subjective feeling finally made sense together.

Some of the improvement clearly came from the cooler weather. The coach estimated that temperature alone could explain part of the difference. The rest was taken as a possible sign of improved fitness.

That distinction matters. It would be tempting to claim a major breakthrough after one faster run. The more honest conclusion is that better conditions allowed me to show more of the fitness that was already there.

One criticism

My recoveries between the harder sections sometimes involved walking rather than slow jogging. ChatGPT suggested using gentle recovery jogs in future sessions.

That would make the workout more specific to half marathon running. The aim is not only to run fast repetitions. It is also to regain rhythm while still moving.

What came next

The next session was supposed to be an easy run of around 8 kilometres. The coach wanted to see whether the improvement also appeared at low intensity.

That was a sensible test. Faster intervals are encouraging, but improved running economy on an ordinary easy day would be stronger evidence that the training was working.

The first session of this experiment was supposed to show ChatGPT what my faster running currently looked like. It also happened to fall on a day when the temperature reached 30°C.

That made it a useful first test. A fixed plan would still have asked for the prescribed pace. A coach looking at the conditions should be more interested in effort, heart rate and whether the repetitions remained controlled.

The session

The original plan called for a warm up, six 800 metre repetitions and a cool down. The surviving record of this workout is incomplete, so I will not pretend that I still have every split. What I can verify is the heart rate, the elevation and the power range during the faster sections.

Metric	Result
Average heart rate	137 bpm
Maximum heart rate	168 bpm
Power during the intervals	Mostly 280 to 300 W
Elevation gain	5 m
Temperature	30°C
How it felt	Hard

The route was almost completely flat, which made the repetitions reasonably comparable. My heart rate rose with each faster section and dropped again during the recoveries. It also crept higher as the session continued.

What the coach saw

ChatGPT interpreted the gradual rise in heart rate as a normal response to the heat rather than evidence that the session had gone wrong. The power remained fairly stable, while pace was more affected by the temperature.

The main conclusion was that I had enough speed for the immediate goal. My ability to hold that speed over longer distances was still the bigger question.

The coach also changed the order of importance for future hot weather sessions. Heart rate and perceived effort would come first, running power second and pace third.

That sounds obvious, but it is easy to do the opposite. A target pace is simple and satisfying. Slowing down because of the weather can feel like missing the workout, even when it is the sensible choice.

What came next

The recommendation was to take a recovery day and run an easy 8 to 9 kilometres on Thursday. The goal was not to hit a particular pace. It was to stay mostly between 125 and 140 bpm and see what pace came naturally.

This first session did not answer whether ChatGPT could coach me to a personal best. It did establish one useful principle: the number written in the plan would not automatically be more important than the conditions on the day.

It all startet here